Graph to Analyse the Relation between a Score and Quantitative Variables

Description

represents the graphs to analyse the relation between a score and quantitative variables.

Usage

```sco.quant (score, df, fac = NULL, clabel = 1, abline = FALSE,
sub = names(df), csub = 2, possub = "topleft")
```

Arguments

 `score` a numeric vector `df` a data frame which rows equal to the score length `fac` a factor with the same length than the score `clabel` character size for the class labels (if any) used with `par("cex")*clabel` `abline` a logical value indicating whether a regression line should be added `sub` a vector of strings of characters for the labels of variables `csub` a character size for the legend, used with `par("cex")*csub` `possub` a string of characters indicating the sub-title position ("topleft", "topright", "bottomleft", "bottomright")

Daniel Chessel

Examples

```w <- runif(100, -5, 10)
fw <- cut (w, 5)
levels(fw) <- LETTERS[1:5]
wX <- data.frame(matrix(w + rnorm(900, sd = (1:900) / 100), 100, 9))
sco.quant(w, wX, fac = fw, abline = TRUE, clab = 2, csub = 3)
```

Worked out examples

```
> ### Name: sco.quant
> ### Title: Graph to Analyse the Relation between a Score and Quantitative
> ###   Variables
> ### Aliases: sco.quant
> ### Keywords: hplot multivariate
>
> ### ** Examples
>
> w <- runif(100, -5, 10)
> fw <- cut (w, 5)
> levels(fw) <- LETTERS[1:5]
> wX <- data.frame(matrix(w + rnorm(900, sd = (1:900) / 100), 100, 9))
> sco.quant(w, wX, fac = fw, abline = TRUE, clab = 2, csub = 3)
```
```>
>
>
>
```