R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-pc-linux-gnu (64-bit) R est un logiciel libre livré sans AUCUNE GARANTIE. Vous pouvez le redistribuer sous certaines conditions. Tapez 'license()' ou 'licence()' pour plus de détails. R est un projet collaboratif avec de nombreux contributeurs. Tapez 'contributors()' pour plus d'information et 'citation()' pour la façon de le citer dans les publications. Tapez 'demo()' pour des démonstrations, 'help()' pour l'aide en ligne ou 'help.start()' pour obtenir l'aide au format HTML. Tapez 'q()' pour quitter R. > date() [1] "Thu Sep 22 16:14:02 2011" > ################################################### > ### chunk number 2: lsdataset > ################################################### > #line 75 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > ls("package:datasets")[1:10] [1] "ability.cov" "airmiles" "AirPassengers" "airquality" [5] "anscombe" "attenu" "attitude" "austres" [9] "beaver1" "beaver2" > > > ################################################### > ### chunk number 3: classcrimtab > ################################################### > #line 95 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > attr(crimtab, "class") [1] "table" > class(crimtab) [1] "table" > > > ################################################### > ### chunk number 4: attrOrange > ################################################### > #line 108 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > attr(Orange, "class") [1] "nfnGroupedData" "nfGroupedData" "groupedData" "data.frame" > class(Orange) [1] "nfnGroupedData" "nfGroupedData" "groupedData" "data.frame" > inherits(Orange,"data.frame") [1] TRUE > > > ################################################### > ### chunk number 5: classpi > ################################################### > #line 132 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > pi [1] 3.141593 > attr(pi, "class") NULL > class(pi) [1] "numeric" > > > ################################################### > ### chunk number 6: classletters > ################################################### > #line 141 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > letters [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" [20] "t" "u" "v" "w" "x" "y" "z" > attr(letters, "class") NULL > class(letters) [1] "character" > > > ################################################### > ### chunk number 7: classinteger > ################################################### > #line 152 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > class(1L) [1] "integer" > class(1) [1] "numeric" > class(1:10) [1] "integer" > > > ################################################### > ### chunk number 8: classlogical > ################################################### > #line 162 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > class(TRUE) [1] "logical" > class(FALSE) [1] "logical" > class(NA) [1] "logical" > > > ################################################### > ### chunk number 9: classlist > ################################################### > #line 170 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > attr(state.center, "class") NULL > class(state.center) [1] "list" > > > ################################################### > ### chunk number 10: dimiris3 > ################################################### > #line 188 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > attr(iris3,"dim") [1] 50 4 3 > dim(iris3) [1] 50 4 3 > class(iris3) [1] "array" > > > ################################################### > ### chunk number 11: classvolcano > ################################################### > #line 199 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dim(volcano) [1] 87 61 > is.array(volcano) [1] TRUE > is.matrix(volcano) [1] TRUE > class(volcano) [1] "matrix" > > > ################################################### > ### chunk number 12: ttest > ################################################### > #line 233 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > t function (x) UseMethod("t") > methods("t") [1] t.data.frame t.default t.ts* Non-visible functions are asterisked > methods(class = "test") no methods were found > > > ################################################### > ### chunk number 13: exfactor > ################################################### > #line 249 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(state.division) Factor w/ 9 levels "New England",..: 4 9 8 5 9 8 1 3 3 3 ... > dput(state.division) structure(c(4L, 9L, 8L, 5L, 9L, 8L, 1L, 3L, 3L, 3L, 9L, 8L, 6L, 6L, 7L, 7L, 4L, 5L, 1L, 3L, 1L, 6L, 7L, 4L, 7L, 8L, 7L, 8L, 1L, 2L, 8L, 2L, 3L, 7L, 6L, 5L, 9L, 2L, 1L, 3L, 7L, 4L, 5L, 8L, 1L, 3L, 9L, 3L, 6L, 8L), .Label = c("New England", "Middle Atlantic", "South Atlantic", "East South Central", "West South Central", "East North Central", "West North Central", "Mountain", "Pacific" ), class = "factor") > str(state.region) Factor w/ 4 levels "Northeast","South",..: 2 4 4 2 4 4 1 2 2 2 ... > dput(state.region) structure(c(2L, 4L, 4L, 2L, 4L, 4L, 1L, 2L, 2L, 2L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 3L, 4L, 3L, 4L, 1L, 1L, 4L, 1L, 2L, 3L, 3L, 2L, 4L, 1L, 1L, 2L, 3L, 2L, 2L, 4L, 1L, 2L, 4L, 2L, 3L, 4L), .Label = c("Northeast", "South", "North Central", "West"), class = "factor") > > > ################################################### > ### chunk number 14: levels > ################################################### > #line 259 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > regions <- state.region > levels(regions) [1] "Northeast" "South" "North Central" "West" > levels(regions) <- c("Nord Est", "Sud", "Centre Nord", "Ouest") > levels(regions) [1] "Nord Est" "Sud" "Centre Nord" "Ouest" > > > ################################################### > ### chunk number 15: statefactor > ################################################### > #line 270 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > par(oma = c(0,0,2,0), mfrow = c(1,2)) > nreg <- length(levels(state.region)) > colreg <- rainbow(nreg)[unclass(state.region)] > plot(state.center, main = "state.region", xlab = "Latitute", + ylab = "Longitude", pch = 21, cex =1.5, las = 1, bg = colreg, + ylim = c(25,60)) > legend("top", inset = 0.01, levels(state.region), pch = 21, ncol = 2, pt.bg = rainbow(nreg)) > ndiv <- length(levels(state.division)) > coldiv <- rainbow(ndiv)[unclass(state.division)] > plot(state.center, main = "state.division", xlab = "Latitute", + ylab = "Longitude", pch = 21, cex =1.5, las = 1, bg = coldiv, + ylim = c(25,60)) > legend("top", inset = 0.01, levels(state.division), pch = 21, ncol = 2, pt.bg = rainbow(ndiv)) > mtext("Les fateurs state.region et state.division", outer = TRUE, + cex = 2) > > > ################################################### > ### chunk number 16: oeso > ################################################### > #line 297 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(esoph$agegp) Ord.factor w/ 6 levels "25-34"<"35-44"<..: 1 1 1 1 1 1 1 1 1 1 ... > dput(esoph$agegp) structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label = c("25-34", "35-44", "45-54", "55-64", "65-74", "75+"), class = c("ordered", "factor")) > > > ################################################### > ### chunk number 17: order > ################################################### > #line 305 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > plot(table(esoph$agegp), lwd = 10, lend = "butt", las = 1, + main = "Effectifs par tranche d'âge", + xlab = "Âge [années]", + ylab = "Effectifs") > > > ################################################### > ### chunk number 18: cut > ################################################### > #line 318 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > cut(rnorm(10), breaks = -3:3, ordered = TRUE) [1] (-2,-1] (-1,0] (0,1] (0,1] (-1,0] (0,1] (2,3] (-1,0] (0,1] [10] (-3,-2] Levels: (-3,-2] < (-2,-1] < (-1,0] < (0,1] < (1,2] < (2,3] > > > ################################################### > ### chunk number 19: exvectnum > ################################################### > #line 328 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(rivers) num [1:141] 735 320 325 392 524 ... > str(stack.loss) num [1:21] 42 37 37 28 18 18 19 20 15 14 ... > str(state.area) num [1:50] 51609 589757 113909 53104 158693 ... > > > ################################################### > ### chunk number 20: exvecchar > ################################################### > #line 336 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(state.abb) chr [1:50] "AL" "AK" "AZ" "AR" "CA" "CO" "CT" "DE" "FL" ... > str(state.name) chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" "California" ... > > > ################################################### > ### chunk number 21: simplevec > ################################################### > #line 343 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dput(stack.loss) c(42, 37, 37, 28, 18, 18, 19, 20, 15, 14, 14, 13, 11, 12, 8, 7, 8, 8, 9, 15, 15) > dput(state.abb) c("AL", "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA", "HI", "ID", "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD", "MA", "MI", "MN", "MS", "MO", "MT", "NE", "NV", "NH", "NJ", "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", "WY") > > > ################################################### > ### chunk number 22: exvectnom > ################################################### > #line 353 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(euro) Named num [1:11] 13.76 40.34 1.96 166.39 5.95 ... - attr(*, "names")= chr [1:11] "ATS" "BEF" "DEM" "ESP" ... > str(islands) Named num [1:48] 11506 5500 16988 2968 16 ... - attr(*, "names")= chr [1:48] "Africa" "Antarctica" "Asia" "Australia" ... > str(precip) Named num [1:70] 67 54.7 7 48.5 14 17.2 20.7 13 43.4 40.2 ... - attr(*, "names")= chr [1:70] "Mobile" "Juneau" "Phoenix" "Little Rock" ... > > > ################################################### > ### chunk number 23: exnames > ################################################### > #line 361 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > names(euro) [1] "ATS" "BEF" "DEM" "ESP" "FIM" "FRF" "IEP" "ITL" "LUF" "NLG" "PTE" > euro["FRF"] FRF 6.55957 > dput(euro) structure(c(13.7603, 40.3399, 1.95583, 166.386, 5.94573, 6.55957, 0.787564, 1936.27, 40.3399, 2.20371, 200.482), .Names = c("ATS", "BEF", "DEM", "ESP", "FIM", "FRF", "IEP", "ITL", "LUF", "NLG", "PTE")) > > abb2name <- state.name > names(abb2name) NULL > names(abb2name) <- state.abb > abb2name["CO"] CO "Colorado" > > > ################################################### > ### chunk number 24: sortdemo > ################################################### > #line 376 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > euro.trie <- sort(euro) > euro.trie["FRF"] FRF 6.55957 > > > ################################################### > ### chunk number 25: exarray > ################################################### > #line 388 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(iris3) num [1:50, 1:4, 1:3] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... - attr(*, "dimnames")=List of 3 ..$ : NULL ..$ : chr [1:4] "Sepal L." "Sepal W." "Petal L." "Petal W." ..$ : chr [1:3] "Setosa" "Versicolor" "Virginica" > > > ################################################### > ### chunk number 26: dimiris > ################################################### > #line 394 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dim(iris3) [1] 50 4 3 > > > ################################################### > ### chunk number 27: dimnairis > ################################################### > #line 401 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dimnames(iris3) [[1]] NULL [[2]] [1] "Sepal L." "Sepal W." "Petal L." "Petal W." [[3]] [1] "Setosa" "Versicolor" "Virginica" > > > ################################################### > ### chunk number 28: acciris3 > ################################################### > #line 408 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > iris3[ , "Sepal L.", "Setosa"] [1] 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9 5.4 4.8 4.8 4.3 5.8 5.7 5.4 5.1 5.7 [20] 5.1 5.4 5.1 4.6 5.1 4.8 5.0 5.0 5.2 5.2 4.7 4.8 5.4 5.2 5.5 4.9 5.0 5.5 4.9 [39] 4.4 5.1 5.0 4.5 4.4 5.0 5.1 4.8 5.1 4.6 5.3 5.0 > > > ################################################### > ### chunk number 29: dputarray > ################################################### > #line 414 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dput(iris3) structure(c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1, 4.8, 5.1, 4.6, 5.3, 5, 3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3, 3, 4, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3, 3.8, 3.2, 3.7, 3.3, 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8, 6, 5.4, 6, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2, 3, 2.2, 2.9, 2.9, 3.1, 3, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3, 2.8, 3, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3, 3.4, 3.1, 2.3, 3, 2.5, 2.6, 3, 2.6, 2.3, 2.7, 3, 2.9, 2.9, 2.5, 2.8, 4.7, 4.5, 4.9, 4, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4, 4.9, 4.7, 4.3, 4.4, 4.8, 5, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4, 4.4, 4.6, 4, 3.3, 4.2, 4.2, 4.2, 4.3, 3, 4.1, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1, 1.3, 1.4, 1, 1.5, 1, 1.4, 1.3, 1.4, 1.5, 1, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1, 1.1, 1, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9, 3.3, 2.7, 3, 2.9, 3, 3, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3, 2.5, 2.8, 3.2, 3, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3, 2.8, 3, 2.8, 3.8, 2.8, 2.8, 2.6, 3, 3.4, 3.1, 3, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3, 2.5, 3, 3.4, 3, 6, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5, 5.1, 5.3, 5.5, 6.7, 6.9, 5, 5.7, 4.9, 6.7, 4.9, 5.7, 6, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5, 5.2, 5.4, 5.1, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2, 1.9, 2.1, 2, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2, 2, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2, 2.3, 1.8), .Dim = c(50L, 4L, 3L), .Dimnames = list( NULL, c("Sepal L.", "Sepal W.", "Petal L.", "Petal W."), c("Setosa", "Versicolor", "Virginica"))) > > > ################################################### > ### chunk number 30: dputtitanic > ################################################### > #line 424 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(Titanic) table [1:4, 1:2, 1:2, 1:2] 0 0 35 0 0 0 17 0 118 154 ... - attr(*, "dimnames")=List of 4 ..$ Class : chr [1:4] "1st" "2nd" "3rd" "Crew" ..$ Sex : chr [1:2] "Male" "Female" ..$ Age : chr [1:2] "Child" "Adult" ..$ Survived: chr [1:2] "No" "Yes" > dput(Titanic) structure(c(0, 0, 35, 0, 0, 0, 17, 0, 118, 154, 387, 670, 4, 13, 89, 3, 5, 11, 13, 0, 1, 13, 14, 0, 57, 14, 75, 192, 140, 80, 76, 20), .Dim = c(4L, 2L, 2L, 2L), .Dimnames = structure(list( Class = c("1st", "2nd", "3rd", "Crew"), Sex = c("Male", "Female" ), Age = c("Child", "Adult"), Survived = c("No", "Yes")), .Names = c("Class", "Sex", "Age", "Survived")), class = "table") > > > ################################################### > ### chunk number 31: hecolor > ################################################### > #line 432 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(HairEyeColor) table [1:4, 1:4, 1:2] 32 53 10 3 11 50 10 30 10 25 ... - attr(*, "dimnames")=List of 3 ..$ Hair: chr [1:4] "Black" "Brown" "Red" "Blond" ..$ Eye : chr [1:4] "Brown" "Blue" "Hazel" "Green" ..$ Sex : chr [1:2] "Male" "Female" > > > ################################################### > ### chunk number 32: extab > ################################################### > #line 439 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(UCBAdmissions) table [1:2, 1:2, 1:6] 512 313 89 19 353 207 17 8 120 205 ... - attr(*, "dimnames")=List of 3 ..$ Admit : chr [1:2] "Admitted" "Rejected" ..$ Gender: chr [1:2] "Male" "Female" ..$ Dept : chr [1:6] "A" "B" "C" "D" ... > > > ################################################### > ### chunk number 33: excrimtab > ################################################### > #line 445 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(crimtab) 'table' int [1:42, 1:22] 0 0 0 0 0 0 1 0 0 0 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:42] "9.4" "9.5" "9.6" "9.7" ... ..$ : chr [1:22] "142.24" "144.78" "147.32" "149.86" ... > > > ################################################### > ### chunk number 34: isarray > ################################################### > #line 457 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > USPersonalExpenditure 1940 1945 1950 1955 1960 Food and Tobacco 22.200 44.500 59.60 73.2 86.80 Household Operation 10.500 15.500 29.00 36.5 46.20 Medical and Health 3.530 5.760 9.71 14.0 21.10 Personal Care 1.040 1.980 2.45 3.4 5.40 Private Education 0.341 0.974 1.80 2.6 3.64 > class(USPersonalExpenditure) [1] "matrix" > is.array(USPersonalExpenditure) [1] TRUE > is.matrix(USPersonalExpenditure) [1] TRUE > dput(USPersonalExpenditure) structure(c(22.2, 10.5, 3.53, 1.04, 0.341, 44.5, 15.5, 5.76, 1.98, 0.974, 59.6, 29, 9.71, 2.45, 1.8, 73.2, 36.5, 14, 3.4, 2.6, 86.8, 46.2, 21.1, 5.4, 3.64), .Dim = c(5L, 5L), .Dimnames = list( c("Food and Tobacco", "Household Operation", "Medical and Health", "Personal Care", "Private Education"), c("1940", "1945", "1950", "1955", "1960"))) > > > ################################################### > ### chunk number 35: VADd > ################################################### > #line 468 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > VADeaths Rural Male Rural Female Urban Male Urban Female 50-54 11.7 8.7 15.4 8.4 55-59 18.1 11.7 24.3 13.6 60-64 26.9 20.3 37.0 19.3 65-69 41.0 30.9 54.6 35.1 70-74 66.0 54.3 71.1 50.0 > > > ################################################### > ### chunk number 36: exmatrix > ################################################### > #line 474 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(WorldPhones) num [1:7, 1:7] 45939 60423 64721 68484 71799 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:7] "1951" "1956" "1957" "1958" ... ..$ : chr [1:7] "N.Amer" "Europe" "Asia" "S.Amer" ... > str(euro.cross) num [1:11, 1:11] 1 0.3411 7.0355 0.0827 2.3143 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" ... ..$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" ... > str(freeny.x) num [1:39, 1:4] 8.8 8.79 8.79 8.81 8.81 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:4] "lag quarterly revenue" "price index" "income level" "market potential" > str(stack.x) num [1:21, 1:3] 80 80 75 62 62 62 62 62 58 58 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:3] "Air.Flow" "Water.Temp" "Acid.Conc." > str(state.x77) num [1:50, 1:8] 3615 365 2212 2110 21198 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" ... ..$ : chr [1:8] "Population" "Income" "Illiteracy" "Life Exp" ... > str(volcano) num [1:87, 1:61] 100 101 102 103 104 105 105 106 107 108 ... > > > ################################################### > ### chunk number 37: exlist > ################################################### > #line 492 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(Harman23.cor) List of 3 $ cov : num [1:8, 1:8] 1 0.846 0.805 0.859 0.473 0.398 0.301 0.382 0.846 1 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ... .. ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ... $ center: num [1:8] 0 0 0 0 0 0 0 0 $ n.obs : num 305 > str(Harman74.cor) List of 3 $ cov : num [1:24, 1:24] 1 0.318 0.403 0.468 0.321 0.335 0.304 0.332 0.326 0.116 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ... .. ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ... $ center: num [1:24] 0 0 0 0 0 0 0 0 0 0 ... $ n.obs : num 145 > str(ability.cov) List of 3 $ cov : num [1:6, 1:6] 24.64 5.99 33.52 6.02 20.75 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:6] "general" "picture" "blocks" "maze" ... .. ..$ : chr [1:6] "general" "picture" "blocks" "maze" ... $ center: num [1:6] 0 0 0 0 0 0 $ n.obs : num 112 > > > ################################################### > ### chunk number 38: exlist2 > ################################################### > #line 503 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(state.center) List of 2 $ x: num [1:50] -86.8 -127.2 -111.6 -92.3 -119.8 ... $ y: num [1:50] 32.6 49.2 34.2 34.7 36.5 ... > head(as.data.frame(state.center)) x y 1 -86.7509 32.5901 2 -127.2500 49.2500 3 -111.6250 34.2192 4 -92.2992 34.7336 5 -119.7730 36.5341 6 -105.5130 38.6777 > head(as.matrix(as.data.frame(state.center))) x y [1,] -86.7509 32.5901 [2,] -127.2500 49.2500 [3,] -111.6250 34.2192 [4,] -92.2992 34.7336 [5,] -119.7730 36.5341 [6,] -105.5130 38.6777 > > > ################################################### > ### chunk number 39: exdf > ################################################### > #line 511 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(BOD) 'data.frame': 6 obs. of 2 variables: $ Time : num 1 2 3 4 5 7 $ demand: num 8.3 10.3 19 16 15.6 19.8 - attr(*, "reference")= chr "A1.4, p. 270" > str(Formaldehyde) 'data.frame': 6 obs. of 2 variables: $ carb : num 0.1 0.3 0.5 0.6 0.7 0.9 $ optden: num 0.086 0.269 0.446 0.538 0.626 0.782 > str(InsectSprays) 'data.frame': 72 obs. of 2 variables: $ count: num 10 7 20 14 14 12 10 23 17 20 ... $ spray: Factor w/ 6 levels "A","B","C","D",..: 1 1 1 1 1 1 1 1 1 1 ... > str(LifeCycleSavings) 'data.frame': 50 obs. of 5 variables: $ sr : num 11.43 12.07 13.17 5.75 12.88 ... $ pop15: num 29.4 23.3 23.8 41.9 42.2 ... $ pop75: num 2.87 4.41 4.43 1.67 0.83 2.85 1.34 0.67 1.06 1.14 ... $ dpi : num 2330 1508 2108 189 728 ... $ ddpi : num 2.87 3.93 3.82 0.22 4.56 2.43 2.67 6.51 3.08 2.8 ... > str(OrchardSprays) 'data.frame': 64 obs. of 4 variables: $ decrease : num 57 95 8 69 92 90 15 2 84 6 ... $ rowpos : num 1 2 3 4 5 6 7 8 1 2 ... $ colpos : num 1 1 1 1 1 1 1 1 2 2 ... $ treatment: Factor w/ 8 levels "A","B","C","D",..: 4 5 2 8 7 6 3 1 3 2 ... > str(PlantGrowth) 'data.frame': 30 obs. of 2 variables: $ weight: num 4.17 5.58 5.18 6.11 4.5 4.61 5.17 4.53 5.33 5.14 ... $ group : Factor w/ 3 levels "ctrl","trt1",..: 1 1 1 1 1 1 1 1 1 1 ... > str(Puromycin) 'data.frame': 23 obs. of 3 variables: $ conc : num 0.02 0.02 0.06 0.06 0.11 0.11 0.22 0.22 0.56 0.56 ... $ rate : num 76 47 97 107 123 139 159 152 191 201 ... $ state: Factor w/ 2 levels "treated","untreated": 1 1 1 1 1 1 1 1 1 1 ... - attr(*, "reference")= chr "A1.3, p. 269" > str(ToothGrowth) 'data.frame': 60 obs. of 3 variables: $ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ... $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ... $ dose: num 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ... > str(USArrests) 'data.frame': 50 obs. of 4 variables: $ Murder : num 13.2 10 8.1 8.8 9 7.9 3.3 5.9 15.4 17.4 ... $ Assault : int 236 263 294 190 276 204 110 238 335 211 ... $ UrbanPop: int 58 48 80 50 91 78 77 72 80 60 ... $ Rape : num 21.2 44.5 31 19.5 40.6 38.7 11.1 15.8 31.9 25.8 ... > str(USJudgeRatings) 'data.frame': 43 obs. of 12 variables: $ CONT: num 5.7 6.8 7.2 6.8 7.3 6.2 10.6 7 7.3 8.2 ... $ INTG: num 7.9 8.9 8.1 8.8 6.4 8.8 9 5.9 8.9 7.9 ... $ DMNR: num 7.7 8.8 7.8 8.5 4.3 8.7 8.9 4.9 8.9 6.7 ... $ DILG: num 7.3 8.5 7.8 8.8 6.5 8.5 8.7 5.1 8.7 8.1 ... $ CFMG: num 7.1 7.8 7.5 8.3 6 7.9 8.5 5.4 8.6 7.9 ... $ DECI: num 7.4 8.1 7.6 8.5 6.2 8 8.5 5.9 8.5 8 ... $ PREP: num 7.1 8 7.5 8.7 5.7 8.1 8.5 4.8 8.4 7.9 ... $ FAMI: num 7.1 8 7.5 8.7 5.7 8 8.5 5.1 8.4 8.1 ... $ ORAL: num 7.1 7.8 7.3 8.4 5.1 8 8.6 4.7 8.4 7.7 ... $ WRIT: num 7 7.9 7.4 8.5 5.3 8 8.4 4.9 8.5 7.8 ... $ PHYS: num 8.3 8.5 7.9 8.8 5.5 8.6 9.1 6.8 8.8 8.5 ... $ RTEN: num 7.8 8.7 7.8 8.7 4.8 8.6 9 5 8.8 7.9 ... > str(airquality) 'data.frame': 153 obs. of 6 variables: $ Ozone : int 41 36 12 18 NA 28 23 19 8 NA ... $ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 ... $ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ... $ Temp : int 67 72 74 62 56 66 65 59 61 69 ... $ Month : int 5 5 5 5 5 5 5 5 5 5 ... $ Day : int 1 2 3 4 5 6 7 8 9 10 ... > str(anscombe) 'data.frame': 11 obs. of 8 variables: $ x1: num 10 8 13 9 11 14 6 4 12 7 ... $ x2: num 10 8 13 9 11 14 6 4 12 7 ... $ x3: num 10 8 13 9 11 14 6 4 12 7 ... $ x4: num 8 8 8 8 8 8 8 19 8 8 ... $ y1: num 8.04 6.95 7.58 8.81 8.33 ... $ y2: num 9.14 8.14 8.74 8.77 9.26 8.1 6.13 3.1 9.13 7.26 ... $ y3: num 7.46 6.77 12.74 7.11 7.81 ... $ y4: num 6.58 5.76 7.71 8.84 8.47 7.04 5.25 12.5 5.56 7.91 ... > str(attenu) 'data.frame': 182 obs. of 5 variables: $ event : num 1 2 2 2 2 2 2 2 2 2 ... $ mag : num 7 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 ... $ station: Factor w/ 117 levels "1008","1011",..: 24 13 15 68 39 74 22 1 8 55 ... $ dist : num 12 148 42 85 107 109 156 224 293 359 ... $ accel : num 0.359 0.014 0.196 0.135 0.062 0.054 0.014 0.018 0.01 0.004 ... > str(attitude) 'data.frame': 30 obs. of 7 variables: $ rating : num 43 63 71 61 81 43 58 71 72 67 ... $ complaints: num 51 64 70 63 78 55 67 75 82 61 ... $ privileges: num 30 51 68 45 56 49 42 50 72 45 ... $ learning : num 39 54 69 47 66 44 56 55 67 47 ... $ raises : num 61 63 76 54 71 54 66 70 71 62 ... $ critical : num 92 73 86 84 83 49 68 66 83 80 ... $ advance : num 45 47 48 35 47 34 35 41 31 41 ... > str(beaver1) 'data.frame': 114 obs. of 4 variables: $ day : num 346 346 346 346 346 346 346 346 346 346 ... $ time : num 840 850 900 910 920 930 940 950 1000 1010 ... $ temp : num 36.3 36.3 36.4 36.4 36.5 ... $ activ: num 0 0 0 0 0 0 0 0 0 0 ... > str(beaver2) 'data.frame': 100 obs. of 4 variables: $ day : num 307 307 307 307 307 307 307 307 307 307 ... $ time : num 930 940 950 1000 1010 1020 1030 1040 1050 1100 ... $ temp : num 36.6 36.7 36.9 37.1 37.2 ... $ activ: num 0 0 0 0 0 0 0 0 0 0 ... > str(cars) 'data.frame': 50 obs. of 2 variables: $ speed: num 4 4 7 7 8 9 10 10 10 11 ... $ dist : num 2 10 4 22 16 10 18 26 34 17 ... > str(chickwts) 'data.frame': 71 obs. of 2 variables: $ weight: num 179 160 136 227 217 168 108 124 143 140 ... $ feed : Factor w/ 6 levels "casein","horsebean",..: 2 2 2 2 2 2 2 2 2 2 ... > str(esoph) 'data.frame': 88 obs. of 5 variables: $ agegp : Ord.factor w/ 6 levels "25-34"<"35-44"<..: 1 1 1 1 1 1 1 1 1 1 ... $ alcgp : Ord.factor w/ 4 levels "0-39g/day"<"40-79"<..: 1 1 1 1 2 2 2 2 3 3 ... $ tobgp : Ord.factor w/ 4 levels "0-9g/day"<"10-19"<..: 1 2 3 4 1 2 3 4 1 2 ... $ ncases : num 0 0 0 0 0 0 0 0 0 0 ... $ ncontrols: num 40 10 6 5 27 7 4 7 2 1 ... > str(faithful) 'data.frame': 272 obs. of 2 variables: $ eruptions: num 3.6 1.8 3.33 2.28 4.53 ... $ waiting : num 79 54 74 62 85 55 88 85 51 85 ... > str(freeny) 'data.frame': 39 obs. of 5 variables: $ y : Time-Series from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ... $ lag.quarterly.revenue: num 8.8 8.79 8.79 8.81 8.81 ... $ price.index : num 4.71 4.7 4.69 4.69 4.64 ... $ income.level : num 5.82 5.83 5.83 5.84 5.85 ... $ market.potential : num 13 13 13 13 13 ... > str(infert) 'data.frame': 248 obs. of 8 variables: $ education : Factor w/ 3 levels "0-5yrs","6-11yrs",..: 1 1 1 1 2 2 2 2 2 2 ... $ age : num 26 42 39 34 35 36 23 32 21 28 ... $ parity : num 6 1 6 4 3 4 1 2 1 2 ... $ induced : num 1 1 2 2 1 2 0 0 0 0 ... $ case : num 1 1 1 1 1 1 1 1 1 1 ... $ spontaneous : num 2 0 0 0 1 1 0 0 1 0 ... $ stratum : int 1 2 3 4 5 6 7 8 9 10 ... $ pooled.stratum: num 3 1 4 2 32 36 6 22 5 19 ... > str(iris) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ... $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ... $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ... $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ... > str(longley) 'data.frame': 16 obs. of 7 variables: $ GNP.deflator: num 83 88.5 88.2 89.5 96.2 ... $ GNP : num 234 259 258 285 329 ... $ Unemployed : num 236 232 368 335 210 ... $ Armed.Forces: num 159 146 162 165 310 ... $ Population : num 108 109 110 111 112 ... $ Year : int 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 ... $ Employed : num 60.3 61.1 60.2 61.2 63.2 ... > str(morley) 'data.frame': 100 obs. of 3 variables: $ Expt : int 1 1 1 1 1 1 1 1 1 1 ... $ Run : int 1 2 3 4 5 6 7 8 9 10 ... $ Speed: int 850 740 900 1070 930 850 950 980 980 880 ... > str(mtcars) 'data.frame': 32 obs. of 11 variables: $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ... $ cyl : num 6 6 4 6 8 6 8 4 4 6 ... $ disp: num 160 160 108 258 360 ... $ hp : num 110 110 93 110 175 105 245 62 95 123 ... $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ... $ wt : num 2.62 2.88 2.32 3.21 3.44 ... $ qsec: num 16.5 17 18.6 19.4 17 ... $ vs : num 0 0 1 1 0 1 0 1 1 1 ... $ am : num 1 1 1 0 0 0 0 0 0 0 ... $ gear: num 4 4 4 3 3 3 3 4 4 4 ... $ carb: num 4 4 1 1 2 1 4 2 2 4 ... > str(pressure) 'data.frame': 19 obs. of 2 variables: $ temperature: num 0 20 40 60 80 100 120 140 160 180 ... $ pressure : num 0.0002 0.0012 0.006 0.03 0.09 0.27 0.75 1.85 4.2 8.8 ... > str(quakes) 'data.frame': 1000 obs. of 5 variables: $ lat : num -20.4 -20.6 -26 -18 -20.4 ... $ long : num 182 181 184 182 182 ... $ depth : int 562 650 42 626 649 195 82 194 211 622 ... $ mag : num 4.8 4.2 5.4 4.1 4 4 4.8 4.4 4.7 4.3 ... $ stations: int 41 15 43 19 11 12 43 15 35 19 ... > str(randu) 'data.frame': 400 obs. of 3 variables: $ x: num 0.000031 0.044495 0.82244 0.322291 0.393595 ... $ y: num 0.000183 0.155732 0.873416 0.648545 0.826873 ... $ z: num 0.000824 0.533939 0.838542 0.990648 0.418881 ... > str(rock) 'data.frame': 48 obs. of 4 variables: $ area : int 4990 7002 7558 7352 7943 7979 9333 8209 8393 6425 ... $ peri : num 2792 3893 3931 3869 3949 ... $ shape: num 0.0903 0.1486 0.1833 0.1171 0.1224 ... $ perm : num 6.3 6.3 6.3 6.3 17.1 17.1 17.1 17.1 119 119 ... > str(sleep) 'data.frame': 20 obs. of 3 variables: $ extra: num 0.7 -1.6 -0.2 -1.2 -0.1 3.4 3.7 0.8 0 2 ... $ group: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ... $ ID : Factor w/ 10 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ... > str(stackloss) 'data.frame': 21 obs. of 4 variables: $ Air.Flow : num 80 80 75 62 62 62 62 62 58 58 ... $ Water.Temp: num 27 27 25 24 22 23 24 24 23 18 ... $ Acid.Conc.: num 89 88 90 87 87 87 93 93 87 80 ... $ stack.loss: num 42 37 37 28 18 18 19 20 15 14 ... > str(swiss) 'data.frame': 47 obs. of 6 variables: $ Fertility : num 80.2 83.1 92.5 85.8 76.9 76.1 83.8 92.4 82.4 82.9 ... $ Agriculture : num 17 45.1 39.7 36.5 43.5 35.3 70.2 67.8 53.3 45.2 ... $ Examination : int 15 6 5 12 17 9 16 14 12 16 ... $ Education : int 12 9 5 7 15 7 7 8 7 13 ... $ Catholic : num 9.96 84.84 93.4 33.77 5.16 ... $ Infant.Mortality: num 22.2 22.2 20.2 20.3 20.6 26.6 23.6 24.9 21 24.4 ... > str(trees) 'data.frame': 31 obs. of 3 variables: $ Girth : num 8.3 8.6 8.8 10.5 10.7 10.8 11 11 11.1 11.2 ... $ Height: num 70 65 63 72 81 83 66 75 80 75 ... $ Volume: num 10.3 10.3 10.2 16.4 18.8 19.7 15.6 18.2 22.6 19.9 ... > str(warpbreaks) 'data.frame': 54 obs. of 3 variables: $ breaks : num 26 30 54 25 70 52 51 26 67 18 ... $ wool : Factor w/ 2 levels "A","B": 1 1 1 1 1 1 1 1 1 1 ... $ tension: Factor w/ 3 levels "L","M","H": 1 1 1 1 1 1 1 1 1 2 ... > str(women) 'data.frame': 15 obs. of 2 variables: $ height: num 58 59 60 61 62 63 64 65 66 67 ... $ weight: num 115 117 120 123 126 129 132 135 139 142 ... > > > ################################################### > ### chunk number 40: dputOrange > ################################################### > #line 556 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > dput(Orange) structure(list(Tree = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("3", "1", "5", "2", "4"), class = c("ordered", "factor")), age = c(118, 484, 664, 1004, 1231, 1372, 1582, 118, 484, 664, 1004, 1231, 1372, 1582, 118, 484, 664, 1004, 1231, 1372, 1582, 118, 484, 664, 1004, 1231, 1372, 1582, 118, 484, 664, 1004, 1231, 1372, 1582), circumference = c(30, 58, 87, 115, 120, 142, 145, 33, 69, 111, 156, 172, 203, 203, 30, 51, 75, 108, 115, 139, 140, 32, 62, 112, 167, 179, 209, 214, 30, 49, 81, 125, 142, 174, 177 )), .Names = c("Tree", "age", "circumference"), row.names = c(NA, 35L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = circumference ~ age | Tree, labels = structure(list( x = "Time since December 31, 1968", y = "Trunk circumference"), .Names = c("x", "y")), units = structure(list(x = "(days)", y = "(mm)"), .Names = c("x", "y"))) > head(Orange) Tree age circumference 1 1 118 30 2 1 484 58 3 1 664 87 4 1 1004 115 5 1 1231 120 6 1 1372 142 > > > ################################################### > ### chunk number 41: orange > ################################################### > #line 566 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > library(nlme) Attachement du package : 'nlme' The following object(s) are masked from 'package:stats': BIC > print(plot(Orange, main = "Croissance de 5 orangers au cours du temps")) > > > ################################################### > ### chunk number 42: CO2plt > ################################################### > #line 578 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > head(CO2) Grouped Data: uptake ~ conc | Plant Plant Type Treatment conc uptake 1 Qn1 Quebec nonchilled 95 16.0 2 Qn1 Quebec nonchilled 175 30.4 3 Qn1 Quebec nonchilled 250 34.8 4 Qn1 Quebec nonchilled 350 37.2 5 Qn1 Quebec nonchilled 500 35.3 6 Qn1 Quebec nonchilled 675 39.2 > print(plot(CO2, main = "Fixation de CO2 par 12 plantes")) > > > ################################################### > ### chunk number 43: chick > ################################################### > #line 588 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > print(plot(ChickWeight, main = "Croissance de poussins")) > > > ################################################### > ### chunk number 44: DNase > ################################################### > #line 597 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > print(plot(DNase, main = "Essais de la DNase")) > > > ################################################### > ### chunk number 45: indo > ################################################### > #line 609 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > print(plot(Indometh, main = "Pharmacocinétique de l'indométacine")) > > > ################################################### > ### chunk number 46: Lob > ################################################### > #line 620 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > data(Loblolly) > Loblolly$height <- Loblolly$height*12*2.54/100 > attr(Loblolly,"units") <- list(x = "(an)", y ="(m)") > attr(Loblolly, "labels") <- list(y = "Hauteur de l'arbre", + x = "Âge de l'arbre") > print(plot(Loblolly, main = "Croissance de 14 pins")) > > > ################################################### > ### chunk number 47: theo > ################################################### > #line 637 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > print(plot(Theoph, main = "Pharmacocinétique de la théophylline")) > > > ################################################### > ### chunk number 48: uspop > ################################################### > #line 656 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > class(uspop) [1] "ts" > str(uspop) Time-Series [1:19] from 1790 to 1970: 3.93 5.31 7.24 9.64 12.9 17.1 23.2 31.4 39.8 50.2 ... > tsp(uspop) [1] 1790.0 1970.0 0.1 > dput(uspop) structure(c(3.93, 5.31, 7.24, 9.64, 12.9, 17.1, 23.2, 31.4, 39.8, 50.2, 62.9, 76, 92, 105.7, 122.8, 131.7, 151.3, 179.3, 203.2), .Tsp = c(1790, 1970, 0.1), class = "ts") > plot(uspop, type = "b", las = 1, xlab = "Année", pch = 19, + ylab = "Population en millions", + main = "Le jeu de données uspop:\n croissance de la population des USA") > > > ################################################### > ### chunk number 49: aps > ################################################### > #line 674 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(AirPassengers) Time-Series [1:144] from 1949 to 1961: 112 118 132 129 121 135 148 148 136 119 ... > tsp(AirPassengers) [1] 1949.000 1960.917 12.000 > (fit <- arima(log10(AirPassengers), c(0, 1, 1), + seasonal = list(order=c(0, 1 ,1), period=12))) Call: arima(x = log10(AirPassengers), order = c(0, 1, 1), seasonal = list(order = c(0, 1, 1), period = 12)) Coefficients: ma1 sma1 -0.4018 -0.5569 s.e. 0.0896 0.0731 sigma^2 estimated as 0.0002543: log likelihood = 353.96, aic = -701.92 > update(fit, method = "CSS") Call: arima(x = log10(AirPassengers), order = c(0, 1, 1), seasonal = list(order = c(0, 1, 1), period = 12), method = "CSS") Coefficients: ma1 sma1 -0.3772 -0.5724 s.e. 0.0883 0.0704 sigma^2 estimated as 0.0002619: part log likelihood = 354.32 > update(fit, x=window(log10(AirPassengers), start = 1954)) Call: arima(x = window(log10(AirPassengers), start = 1954), order = c(0, 1, 1), seasonal = list(order = c(0, 1, 1), period = 12)) Coefficients: ma1 sma1 -0.4797 -0.4460 s.e. 0.1000 0.1514 sigma^2 estimated as 0.0001603: log likelihood = 208.02, aic = -410.04 > pred <- predict(fit, n.ahead = 24) > tl <- pred$pred - 1.96 * pred$se > tu <- pred$pred + 1.96 * pred$se > par(las=1) > ts.plot(AirPassengers, 10^tl, 10^tu, log = "y", lty = c(1,2,2), + col = c("black", "red", "red"), + xlab = "Temps", + ylab = "Milliers de voyageurs", + main = "Nombre mensuel de voyageurs sur des vols internationaux") > legend("topleft", inset = 0.01, c("Observé", "Prédiction"), col = c("black", "red"), + lty = c(1,2)) > > > ################################################### > ### chunk number 50: aps2 > ################################################### > #line 697 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(AirPassengers, + main = "Nombre de voyageurs aériens mensuels (1949 à 1960)", + las = 1, ylab = "Passagers [milliers]", + xlab = "Mois", type = "h") > > > ################################################### > ### chunk number 51: BJ > ################################################### > #line 712 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(BJsales) Time-Series [1:150] from 1 to 150: 200 200 199 199 199 ... > str(BJsales.lead) Time-Series [1:150] from 1 to 150: 10.01 10.07 10.32 9.75 10.33 ... > > > ################################################### > ### chunk number 52: jj > ################################################### > #line 720 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(JohnsonJohnson) Time-Series [1:84] from 1960 to 1981: 0.71 0.63 0.85 0.44 0.61 0.69 0.92 0.55 0.72 0.77 ... > tsp(JohnsonJohnson) [1] 1960.00 1980.75 4.00 > > > ################################################### > ### chunk number 53: lh > ################################################### > #line 732 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(LakeHuron) Time-Series [1:98] from 1875 to 1972: 580 582 581 581 580 ... > tsp(LakeHuron) [1] 1875 1972 1 > par(mar = c(5,6,4,2)+0.1) > plot(LakeHuron*12/254, type = "b", pch = 19, las =1, + xlab = "Année", + ylab = "", + main = "Variation du niveau du lac Huron") > title(ylab = "Niveau [m]", line = 5) > > > ################################################### > ### chunk number 54: nil > ################################################### > #line 754 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(Nile) Time-Series [1:100] from 1871 to 1970: 1120 1160 963 1210 1160 1160 813 1230 1370 1140 ... > tsp(Nile) [1] 1871 1970 1 > plot(Nile, type = "b", pch = 19, + main = "Débit annuel du Nil à Assouan", + xlab = "Année", ylab = expression(paste("Débit [", 10^8, m^3, "]"))) > x0 <- 1871 > x1 <- 1898 > y <- mean(window(Nile, x0, x1)) > segments(x0,y,x1,y, col = "red") > x0 <- 1899 > x1 <- 1970 > y <- mean(window(Nile, x0, x1)) > segments(x0,y,x1,y, col = "red") > > > ################################################### > ### chunk number 55: ukd > ################################################### > #line 783 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(UKDriverDeaths) Time-Series [1:192] from 1969 to 1985: 1687 1508 1507 1385 1632 ... > tsp(UKDriverDeaths) [1] 1969.000 1984.917 12.000 > plot(UKDriverDeaths, ylim = c(0, max(UKDriverDeaths)),las=1, ylab = "", + main = "Nombre de conducteurs morts ou gravement blessés en Grande-Bretagne") > abline(v = 1983+1/12, col = "red", ylab = "") > legend("bottom", inset = 0.1, + "Port de la ceinture obligatoire", lty =1, + col = "red") > > > ################################################### > ### chunk number 56: ukd2 > ################################################### > #line 800 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(UKDriverDeaths/1000, type="h", las = 1, + xlab = "Mois de l'année", + main = "Fluctuations saisonnières des conducteurs morts en Grande-Bretagne", + ylab = "Nombre de morts [millier]") > > > ################################################### > ### chunk number 57: ukg > ################################################### > #line 812 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(UKgas) Time-Series [1:108] from 1960 to 1987: 160.1 129.7 84.8 120.1 160.1 ... > tsp(UKgas) [1] 1960.00 1986.75 4.00 > plot(UKgas, + main = "Consommation trimestrielle de gaz naturel en Grande-Bretagne", las = 1, xlab = "Année", ylab = "") > > > ################################################### > ### chunk number 58: ukg2 > ################################################### > #line 824 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(UKgas, + main = "Fluctuations saisonnières de la consommation de gaz naturel", las = 1, xlab = "Trimestres", ylab = "", type = "h") > > > ################################################### > ### chunk number 59: usacc > ################################################### > #line 833 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(USAccDeaths) Time-Series [1:72] from 1973 to 1979: 9007 8106 8928 9137 10017 ... > tsp(USAccDeaths) [1] 1973.000 1978.917 12.000 > plot(USAccDeaths/1000, type = "b", pch = 19, + xlab = "Années", las = 1, + main = "Nombre de morts accidentelles aux USA", + ylab = "Morts [milliers]") > > > ################################################### > ### chunk number 60: usacc2 > ################################################### > #line 849 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(USAccDeaths/1000, type = "h", + xlab = "Mois de l'année", las = 1, + main = "Fluctuation saisonnières du nombre de morts accidentelles aux USA", + ylab = "Morts [milliers]") > > > ################################################### > ### chunk number 61: www > ################################################### > #line 862 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(WWWusage) Time-Series [1:100] from 1 to 100: 88 84 85 85 84 85 83 85 88 89 ... > tsp(WWWusage) [1] 1 100 1 > plot(WWWusage, type = "b", pch = 19, + xlab = "Temps [mn]", las = 1, + main = "Charge d'un serveur Internet", + ylab = "Nombre d'utilisateurs") > > > ################################################### > ### chunk number 62: airm > ################################################### > #line 878 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(airmiles) Time-Series [1:24] from 1937 to 1960: 412 480 683 1052 1385 ... > tsp(airmiles) [1] 1937 1960 1 > > > ################################################### > ### chunk number 63: aus > ################################################### > #line 887 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(austres) Time-Series [1:89] from 1971 to 1993: 13067 13130 13198 13254 13304 ... > tsp(austres) [1] 1971.25 1993.25 4.00 > plot(austres/1000, type="b", las = 1, + xlab ="Année", pch = 19, + ylab = "Résidents [millions]", + main = "Croissance du nombre de résidents australiens") > > > ################################################### > ### chunk number 64: co2 > ################################################### > #line 906 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(co2) Time-Series [1:468] from 1959 to 1998: 315 316 316 318 318 ... > tsp(co2) [1] 1959.000 1997.917 12.000 > plot(co2, las = 1, + xlab ="Année", + ylab = "Concentration [ppm]", + main = expression("Concentration atmosphérique en CO"[2])) > > > ################################################### > ### chunk number 65: co22 > ################################################### > #line 920 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > plot(co2, las = 1, + xlab ="Année", + ylab = "Concentration [ppm]", + ylim = c(0, max(co2)), + main = expression("Concentration atmosphérique en CO"[2])) > > > ################################################### > ### chunk number 66: co23 > ################################################### > #line 933 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(co2, las = 1, + xlab ="Mois de l'année", + ylab = "Concentration [ppm]", + main = expression("Fluctuations saisonnières de la concentration en CO"[2])) > > > ################################################### > ### chunk number 67: disco > ################################################### > #line 945 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(discoveries) Time-Series [1:100] from 1860 to 1959: 5 3 0 2 0 3 2 3 6 1 ... > tsp(discoveries) [1] 1860 1959 1 > plot(discoveries, las = 1,type="s", + xlab ="Année", + ylab = "Nombre d'innovations par an", + main = "Nombre d'innovations scientifiques majeures") > polycurve <- function(x, y, base.y = min(y), ...) { + polygon(x = c(min(x), x, max(x)), y = c(base.y, y, base.y), + ...) + } > x <- time(discoveries) > x <- rep(x, each=2) > x[c(F,T)] <- x[c(F,T)]+1 > y <- rep(discoveries, each=2) > polycurve(x = x, y, col = grey(0.7)) > > > ################################################### > ### chunk number 68: tot > ################################################### > #line 973 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(ldeaths) Time-Series [1:72] from 1974 to 1980: 3035 2552 2704 2554 2014 ... > str(fdeaths) Time-Series [1:72] from 1974 to 1980: 901 689 827 677 522 406 441 393 387 582 ... > str(mdeaths) Time-Series [1:72] from 1974 to 1980: 2134 1863 1877 1877 1492 ... > tsp(ldeaths) [1] 1974.000 1979.917 12.000 > tsp(fdeaths) [1] 1974.000 1979.917 12.000 > tsp(mdeaths) [1] 1974.000 1979.917 12.000 > tot <- ts(matrix(c(ldeaths,mdeaths,fdeaths),ncol=3), + names = c("Total", "Mâles", "Femelles")) > tsp(tot) <- tsp(ldeaths) > plot(tot/1000, main = "Nombre de décès par maladie pulmonaire en Grande-Bretagne", xlab = "Année") > > > ################################################### > ### chunk number 69: ldeaths > ################################################### > #line 992 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(ldeaths/1000, type = "h", main = "Fluctuations saisonnières de la série ldeaths", xlab = "Mois de l'année") > > > ################################################### > ### chunk number 70: freeny > ################################################### > #line 1000 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(freeny.y) Time-Series [1:39] from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ... > tsp(freeny.y) [1] 1962.25 1971.75 4.00 > > > ################################################### > ### chunk number 71: lh > ################################################### > #line 1026 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(lh) Time-Series [1:48] from 1 to 48: 2.4 2.4 2.4 2.2 2.1 1.5 2.3 2.3 2.5 2 ... > tsp(lh) [1] 1 48 1 > plot(lh, ylim = c(0,6), ylab = "LH", main = "Les données de data(lh)") > > > ################################################### > ### chunk number 72: lynx > ################################################### > #line 1048 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(lynx) Time-Series [1:114] from 1821 to 1934: 269 321 585 871 1475 ... > tsp(lynx) [1] 1821 1934 1 > par(mar = c(2,5,1,1)+0.1) > plot(lynx, las = 1, ylab = "Population (Log)", log = "y") > > > ################################################### > ### chunk number 73: nhtemp > ################################################### > #line 1062 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(nhtemp) Time-Series [1:60] from 1912 to 1971: 49.9 52.3 49.4 51.1 49.4 47.9 49.8 50.9 49.3 51.9 ... > tsp(nhtemp) [1] 1912 1971 1 > nhtemp.C <- 5*(nhtemp-32)/9 > plot(nhtemp.C, + xlab = "Année", + ylab = "Température [C]", + main = "Températures annuelles moyennes à New Haven", las = 1, + type = "b", pch = 19) > lines(lowess(nhtemp.C), lwd = 2, col = "red") > > > ################################################### > ### chunk number 74: not > ################################################### > #line 1082 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(nottem) Time-Series [1:240] from 1920 to 1940: 40.6 40.8 44.4 46.7 54.1 58.5 57.7 56.4 54.3 50.5 ... > tsp(nottem) [1] 1920.000 1939.917 12.000 > nottem.C <- 5*(nottem-32)/9 > plot(nottem.C, + xlab = "Année", + ylab = "Température [C]", las = 1, + type = "l", + main = "Températures mensuelles moyennes à Nottingham") > > > ################################################### > ### chunk number 75: not2 > ################################################### > #line 1096 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > monthplot(nottem.C, + main = "Températures mensuelles moyennes à Nottingham (1920-1940)", + las = 1, ylab = "Température [C]", + xlab = "Mois", type = "h") > > > ################################################### > ### chunk number 76: presi > ################################################### > #line 1111 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(presidents) Time-Series [1:120] from 1945 to 1975: NA 87 82 75 63 50 43 32 35 60 ... > tsp(presidents) [1] 1945.00 1974.75 4.00 > plot(presidents, type = "b", pch=19, + las = 1, xlab = "Année", ylab = "Cote", + main="Cote de popularité des présidents des USA") > abline(h=50, col = "red") > > > ################################################### > ### chunk number 77: sunspotsinfos > ################################################### > #line 1141 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(sunspots) Time-Series [1:2820] from 1749 to 1984: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ... > tsp(sunspots) [1] 1749.000 1983.917 12.000 > str(sunspot.month) Time-Series [1:2988] from 1749 to 1998: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ... > tsp(sunspot.month) [1] 1749.000 1997.917 12.000 > str(sunspot.year) Time-Series [1:289] from 1700 to 1988: 5 11 16 23 36 58 29 20 10 8 ... > tsp(sunspot.year) [1] 1700 1988 1 > > > ################################################### > ### chunk number 78: sun1 > ################################################### > #line 1150 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > plot(sunspots, + main = "La série sunspots", + xlab = "Temps [année]", + las = 1, ylab = "") > > > ################################################### > ### chunk number 79: sun2 > ################################################### > #line 1160 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > plot(sunspot.month, + main = "La série sunspot.month", + xlab = "Temps [année]", + las = 1, ylab = "") > > > ################################################### > ### chunk number 80: sun3 > ################################################### > #line 1168 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > plot(sunspot.year, + main = "La série sunspot.year", + xlab = "Temps [année]", + las = 1, ylab = "") > > > ################################################### > ### chunk number 81: ests > ################################################### > #line 1180 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(treering) Time-Series [1:7980] from -6000 to 1979: 1.34 1.08 1.54 1.32 1.41 ... > > > ################################################### > ### chunk number 82: seat > ################################################### > #line 1201 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(Seatbelts) mts [1:192, 1:8] 107 97 102 87 119 106 110 106 107 134 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:8] "DriversKilled" "drivers" "front" "rear" ... - attr(*, "tsp")= num [1:3] 1969 1985 12 - attr(*, "class")= chr [1:2] "mts" "ts" > tsp(Seatbelts) [1] 1969.000 1984.917 12.000 > plot(Seatbelts) > > > ################################################### > ### chunk number 83: eust > ################################################### > #line 1211 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(EuStockMarkets) mts [1:1860, 1:4] 1629 1614 1607 1621 1618 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:4] "DAX" "SMI" "CAC" "FTSE" - attr(*, "tsp")= num [1:3] 1991 1999 260 - attr(*, "class")= chr [1:2] "mts" "ts" > tsp(EuStockMarkets) [1] 1991.496 1998.646 260.000 > plot(EuStockMarkets) > > > ################################################### > ### chunk number 84: exdist > ################################################### > #line 1224 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > str(eurodist) Class 'dist' atomic [1:210] 3313 2963 3175 3339 2762 ... ..- attr(*, "Size")= num 21 ..- attr(*, "Labels")= chr [1:21] "Athens" "Barcelona" "Brussels" "Calais" ... > dput(eurodist) structure(c(3313, 2963, 3175, 3339, 2762, 3276, 2610, 4485, 2977, 3030, 4532, 2753, 3949, 2865, 2282, 2179, 3000, 817, 3927, 1991, 1318, 1326, 1294, 1498, 2218, 803, 1172, 2018, 1490, 1305, 645, 636, 521, 1014, 1365, 1033, 1460, 2868, 1802, 204, 583, 206, 966, 677, 2256, 597, 172, 2084, 690, 1558, 1011, 925, 747, 285, 1511, 1616, 1175, 460, 409, 1136, 747, 2224, 714, 330, 2052, 739, 1550, 1059, 1077, 977, 280, 1662, 1786, 1381, 785, 1545, 853, 2047, 1115, 731, 1827, 789, 1347, 1101, 1209, 1160, 340, 1794, 2196, 1588, 760, 1662, 2436, 460, 269, 2290, 714, 1764, 1035, 911, 583, 465, 1497, 1403, 937, 1418, 3196, 460, 269, 2971, 1458, 2498, 1778, 1537, 1104, 1176, 2050, 650, 1455, 1975, 1118, 895, 1936, 158, 1439, 425, 328, 591, 513, 995, 2068, 1019, 2897, 2428, 676, 1817, 698, 1693, 2185, 2565, 1971, 2631, 3886, 2974, 550, 2671, 1159, 2198, 1479, 1238, 805, 877, 1751, 949, 1155, 2280, 863, 1730, 1183, 1098, 851, 457, 1683, 1500, 1205, 1178, 668, 1762, 2250, 2507, 1799, 2700, 3231, 2937, 1281, 320, 328, 724, 471, 1048, 2108, 1157, 1157, 1724, 2010, 1273, 2097, 3188, 2409, 618, 1109, 792, 1011, 2428, 1363, 331, 856, 586, 2187, 898, 821, 946, 1754, 428, 1476, 1827, 1249, 2707, 1209, 2105), Size = 21, Labels = c("Athens", "Barcelona", "Brussels", "Calais", "Cherbourg", "Cologne", "Copenhagen", "Geneva", "Gibraltar", "Hamburg", "Hook of Holland", "Lisbon", "Lyons", "Madrid", "Marseilles", "Milan", "Munich", "Paris", "Rome", "Stockholm", "Vienna"), class = "dist") > > > ################################################### > ### chunk number 85: nnm > ################################################### > #line 1234 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > (n <- attr(eurodist, "Size")) [1] 21 > n*(n-1)/2 == length(eurodist) [1] TRUE > > > ################################################### > ### chunk number 86: asmatdist > ################################################### > #line 1244 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > as.matrix(eurodist)[1:5, 1:5] Athens Barcelona Brussels Calais Cherbourg Athens 0 3313 2963 3175 3339 Barcelona 3313 0 1318 1326 1294 Brussels 2963 1318 0 204 583 Calais 3175 1326 204 0 460 Cherbourg 3339 1294 583 460 0 > i <- 3 > j <- 4 > as.matrix(eurodist)[i,j] [1] 204 > eurodist[n*(i-1) - i*(i-1)/2 + j-i] [1] 204 > > > ################################################### > ### chunk number 87: labelsetc > ################################################### > #line 1259 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > data(eurodist) > labels(eurodist) [1] "Athens" "Barcelona" "Brussels" "Calais" [5] "Cherbourg" "Cologne" "Copenhagen" "Geneva" [9] "Gibraltar" "Hamburg" "Hook of Holland" "Lisbon" [13] "Lyons" "Madrid" "Marseilles" "Milan" [17] "Munich" "Paris" "Rome" "Stockholm" [21] "Vienna" > attr(eurodist, "Labels")[13] <- "Lyon" > labels(eurodist) [1] "Athens" "Barcelona" "Brussels" "Calais" [5] "Cherbourg" "Cologne" "Copenhagen" "Geneva" [9] "Gibraltar" "Hamburg" "Hook of Holland" "Lisbon" [13] "Lyon" "Madrid" "Marseilles" "Milan" [17] "Munich" "Paris" "Rome" "Stockholm" [21] "Vienna" > > > ################################################### > ### chunk number 88: eurodist1 > ################################################### > #line 1269 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > par(yaxt="n") > plot(hclust(eurodist,method="average"),ann=F) > > > ################################################### > ### chunk number 89: fortune > ################################################### > #line 1279 "/bge/penel/verif_pedadoc/pedadoc/fichestd/tdr1e//tdr1e.rnw" > library(fortunes) Erreur dans library(fortunes) : aucun package nommé 'fortunes' n'est trouvé Exécution arrêtée