Hello, to our english speaking ADE-users
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The main modifications in the version 98 concern:
1) Correspondence analysis of correspondence with a column of reference, in
the CA family on models (Escofier, B. 1984. Analyse factorielle en
référence à un modèle.
Applications à l'analyse d'un tableau d'échanges. Revue de Statistique
Appliquée: 32, 4, 25-36). Implementation in COA: ColumnReference,
Detailed explanations in the form Thema2C.
2) PCA on fuzzy variables. The question is posed by the manipulation
of species-traits or species-ecological profiles tables. The option
FuzzyVar: Fuzzy Centring centers these tables in a logic of PCA. The
option PCA: Fuzzy PCA makes a PCA centered using assistance with the
specific interpretation. These options allow to process these tables by
way of K-sets methods. This operation is explained in the form Thema81
(Part 8 - under way development). The option Tables: FuzzyVariables
allows to visualize these tables.
3) Classic canonical analysis. It is available in Canonical: Canonical
correlations Analysis. The option reproduces the essential of calculations
described in the work of reference (Gittins, R. 1985. Canonical analysis, a
review with applications in ecology. Springer-Verlag, Berlin. 1-351)
4) Generalized canonical analysis, extension of the previous analysis for
K-tables (Carrol, J.D. 1968. A generalization of canonical correlation
analysis to three or more sets of variables. Proceeding of the 76th
Convention of the American
Psychological Association: 3, 227-228). Interpretation assistance
uses proposals of Casin, Ph. & Turlot, J.C. 1986. Une présentation de
l'analyse canonique généralisée dans l'espace des individus. Revue de
Statistique Appliquée: XXXV, 3, 65-75.
5) Matrices of correlation between tables. Canonical: CC coefficients
calculates matrices of correlation coefficients of the canonical
analysis, Canonical: RLS coefficients calculates matrices of coefficient
RLS (Kiers, H.A.L, Cléroux, R. & Ten Berge, M.F. (1994) Generalized
analysis based on optimizing matrix correlations and a relation with IDIOSCAL.
Computational Statistics and Data Analysis: 18, 331-340) and Canonical:
RV coefficients calculates matrices of RV coefficents. This last option is
a lightened version of the program ACT-STATIS centered on the
investigation of the interstructure. The module form gives definitions and
references.
Thank you to H. Kiers for its theoretical indications reported
in the module form.
6) Processing of lists of occurrences. The module OccurData allows to
approach ecological data when there are no longer samples, but solely
lists of occurrences (for example the recording of collection copies, the
plant collections,Š). OccurData: Read_Occur_File initiates procedures,
OccurData: CANOCO-Classes analyzes the list of occurrences according to a
partition (for example geographical), OccurData: CANOCO-Table analyzes the
list of occurrences when one has
environmental records associated to each occurrence, OccurData:
CANOCO-Subspace makes the same thing by using projeciton. The form Thema49
gives reasons for the choice of CANOCO as title of these analyses because
proposed analyses are true canonical analyses. This allows to indicate in
the form Thema4A when and why canonical correspondence analysis is a
canonical analysis. These innovations are part of the thesis of C.
Gimaret. OccurData: Array_to_Occur allows to transform the
species-by-samples tables in list of occurrences and to see that to choose
the CA and the CCA in ecology it is essentially considered that the
statistical unit is rather the occurrence of a taxon than the sample
itself. Such tools were formerly introduced by Green, R.H. 1971. A
multivariate statistical approach to the Hutchinsonian niche: bivalve
Molluscs of Central Canada. Ecology: 52, 543-556.
7) Analysis of the match between K tables and one table. The module
K+1 allows to introduce operators of co - inertia (X1, Y), (X2, Y),Š, (Xk,
Y) in an analysis of multiple coinertia analysis what finds the analysis of
concordances of Lafosse, R. & Hanafi, M. 1997. Concordance d'un tableau
avec K tableaux: définition de K+1 uples synthétiques. Revue de
Statistique Appliquée: (in press). With these implementations, ADE-4
contains now a panoply complete enough of K-sets methods.
Miscellaneous modifications:
CategVar: Read Categ File
files moda.cat and moda.123 are in option
COA: Internal COA
formats of publishing were improved
FilesUtil: Row_Duplicate
to copy rows of a table in function of a qualitative variable (tsee the
card of the pile info.hyp)
Graph1D: Match_2_var
to represent two numerical codes on one axis (example Thema49 p. 24)
Graph1D: Between_Graph
to represent a numerical code on one axis according to a partition (example
Thema49 p. 26)
Graph1D: Scal_2_scor
to represent two numerical codes on one axis (after standardization)
KTabUtil: MatchKTab-Tab
to associate K-tables and one table
Levels: Selected value
to trace a level curve given its value
Levels: Evenly spaced values
to trace level curves evenly spaced
OccurData: Rare_Species
to extract rare species from a list of occurences
Projectors: XY- > Orthonormal Basis - to get an orthonormal basis from
polynomials in x and y and to introduce the spatial coordinates in
canonical analyses (Wartenberg, D.E. 1985a. Canonical trend surface
analysis: a method for describing geographic
pattern. Systematic Zoology: 34 (3), 259-279)
Scatters: Labels
to trace a '+' sign in each point by typing value 3 in the dialogue box
'Draw points'
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HAVE FUN!
_____________________________________________
Sylvain Dolédec
Universite Claude Bernard Lyon 1
Bat 401C
69622 Villeurbanne CEDEX - France
Tel : (33) 4 72 43 13 63
Fax : (33) 4 72 43 11 41
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ADE-4 package is available on the Internet
--> http://pbil.univ-lyon1.fr/ADE-4/
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