# pfa: Principal Factor Analysis In StatDA: Statistical Analysis for Environmental Data

 pfa R Documentation

## Principal Factor Analysis

### Description

Computes the principal factor analysis of the input data.

### Usage

``````pfa(x, factors, data = NULL, covmat = NULL, n.obs = NA, subset, na.action,
start = NULL, scores = c("none", "regression", "Bartlett"),
rotation = "varimax", maxiter = 5, control = NULL, ...)
``````

### Arguments

 `x` (robustly) scaled input data `factors` number of factors `data` default value is NULL `covmat` (robustly) computed covariance or correlation matrix `n.obs` number of observations `subset` if a subset is used `start` starting values `scores` which method should be used to calculate the scores `rotation` if a rotation should be made `maxiter` maximum number of iterations `control` default value is NULL `na.action` what to do with NA values `...` arguments for creating a list

### Value

 `loadings` A matrix of loadings, one column for each factor. The factors are ordered in decreasing order of sums of squares of loadings. `uniquness` uniquness `correlation` correlation matrix `criteria` The results of the optimization: the value of the negativ log-likelihood and information of the iterations used. `factors` the factors `dof` degrees of freedom `method` "principal" `n.obs` number of observations if available, or NA `call` The matched call. `STATISTIC, PVAL` The significance-test statistic and p-value, if can be computed

### Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at> http://cstat.tuwien.ac.at/filz/

### References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

### Examples

``````data(moss)
var=c("Ni","Cu","Mg","Rb","Mn")
x=log10(moss[,var])

x.mcd=robustbase::covMcd(x,cor=TRUE)
x.rsc=scale(x,x.mcd\$cent,sqrt(diag(x.mcd\$cov)))
pfa(x.rsc,factors=2,covmat=x.mcd,scores="regression",rotation="varimax",
maxit=0,start=rep(0,ncol(x.rsc)))

``````

StatDA documentation built on June 7, 2023, 6:26 p.m.