ade4 (version 1.5-2)

sco.gauss: Relationships between one score and qualitative variables

Description

Draws Gauss curves with the same mean and variance as the scores of indivivuals belonging to categories of several qualitative variables.

Usage

sco.gauss(score, df, xlim = NULL, steps = 200, ymax = NULL, sub =
names(df), csub = 1.25, possub = "topleft", legen =TRUE, label = row.names(df),
clabel = 1, grid = TRUE, cgrid = 1, include.origin = TRUE, origin = c(0, 0))

Arguments

score

a numeric vector

df

a dataframe containing only factors, number of rows equal to the length of the score vector

xlim

starting point and end point for drawing the Gauss curves

steps

number of segments for drawing the Gauss curves

ymax

max ordinate for all Gauss curves. If NULL, ymax is computed and different for each factor

sub

vector of strings of characters for the lables of qualitative variables

csub

character size for the legend

possub

a string of characters indicating the sub-title position ("topleft", "topright", "bottomleft", "bottomright")

legen

if TRUE, the first graphic of the series displays the score with evenly spaced labels (see sco.label)

label

labels for the score

clabel

a character size for the labels, used with par("cex")*clabel

grid

a logical value indicating whether a grid in the background of the plot should be drawn

cgrid

a character size, parameter used with par("cex")*cgrid to indicate the mesh of the grid

include.origin

a logical value indicating whether the point "origin" should belong to the plot

origin

the fixed point in the graph space, for example c(0,0) the origin axes

Value

• The matched call.

Details

Takes one vector containing quantitative values (score) and one dataframe containing only factors that give categories to wich the quantitative values belong. Computes the mean and variance of the values in each category of each factor, and draws a Gauss curve with the same mean and variance for each category of each factor. Can optionaly set the start and end point of the curves and the number of segments. The max ordinate (ymax) can also be set arbitrarily to set a common max for all factors (else the max is different for each factor).

Examples

data(meau)
envpca <- dudi.pca(meau$env, scannf=FALSE)
dffac <- cbind.data.frame(meau$design$season, meau$design$site)
sco.gauss(envpca$li[,1], dffac, clabel = 2, csub = 2)