ade4 (version 1.7-19)

scalewt: Compute or scale data using (weighted) means, variances and covariances (possibly for the levels of a factor)

Description

These utility functions compute (weighted) means, variances and covariances for dataframe partitioned by a factor. The scale transforms a numeric matrix in a centred and scaled matrix for any weighting.

Usage

covwt(x, wt, na.rm = FALSE)
varwt(x, wt, na.rm = FALSE)
scalewt(df, wt = rep(1/nrow(df), nrow(df)), center = TRUE, scale = TRUE)
meanfacwt(df, fac = NULL, wt = rep(1/nrow(df), nrow(df)), drop = FALSE)
varfacwt(df, fac = NULL, wt = rep(1/nrow(df), nrow(df)), drop = FALSE)
covfacwt(df, fac = NULL, wt = rep(1/nrow(df), nrow(df)), drop = FALSE)
scalefacwt(df, fac = NULL, wt = rep(1/nrow(df), nrow(df)), scale = TRUE, drop = FALSE)

Value

For varwt, the weighted variance. For covwt, the matrix of weighted co-variances. For scalewt, the scaled dataframe. For other function a list (if fac is not null) of dataframes with approriate values

Arguments

x

a numeric vector (varwt) or a matrix (covwt) containg the data.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

df

a matrix or a dataframe containing the data.

fac

a factor partitioning the data.

wt

a numeric vector of weights.

drop

a logical value indicating whether unused levels should be kept.

scale

a logical value indicating whether data should be scaled or not.

center

a logical value indicating whether data should be centered or not.

Author

Stéphane Dray

Details

Functions returns biased estimates of variances and covariances (i.e. divided by n and not n-1)

Examples

data(meau)
w <- rowSums(meau$spe)
varwt(meau$env, w)
varfacwt(meau$env, wt = w)
varfacwt(meau$env, wt = w, fac = meau$design$season)
covfacwt(meau$env, wt = w, fac = meau$design$season)
scalewt(meau$env, wt = w)