ade4: sco.gauss – R documentation

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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

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).

Value

The matched call.

Author(s)

Jean Thioulouse, Stéphane Dray stephane.dray@univ-lyon1.fr

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)

ade4

Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

v1.7-16

GPL (>= 2)

Authors

Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.

Initial release