# computeScores: Compute Factor Scores In robustfa: Object Oriented Solution for Robust Factor Analysis

 computeScores R Documentation

## Compute Factor Scores

### Description

Compute factor scores on the result of factor analysis method, the method is one of "mle", "pca", and "pfa".

### Usage

``````computeScores(out, x = data, covmat = covmat, cor = cor, scoresMethod = scoresMethod)
``````

### Arguments

 `out` The result of factorScorePca(), factorScorePfa(), or factanal(). It is a list. `x` A numeric matrix. `covmat` A list with components: cov, center, and n.obs. `cor` A logical value indicating whether the calculation should use the covariance matrix (`cor = FALSE`) or the correlation matrix (`cor = TRUE`). `scoresMethod` Type of scores to produce, if any. The default is `"none"`, `"regression"` gives Thompson's scores, `"Bartlett"` gives Bartlett's weighted least-squares scores.

### Value

The output is a list. Except for the components of `out`, it also has components:

 `scoringCoef ` The scoring coefficients. `scores ` The matrix of scores. `meanF ` The sample mean of the scores. `corF ` The sample correlation matrix of the scores. `eigenvalues ` The eigenvalues of the running matrix. `covariance ` The covariance matrix. `correlation ` The correlation matrix. `usedMatrix ` The used matrix (running matrix) to compute `scoringCoef` etc.. `reducedCorrelation ` NULL. The reduced correlation matrix, reducedCorrelation is calculated in factorScorePfa.R.

scoringCoef = F = meanF = corF = NULL if `scoresMethod = "none"`.

### Author(s)

Ying-Ying Zhang (Robert) robertzhangyying@qq.com

### References

Zhang, Y. Y. (2013), An Object Oriented Solution for Robust Factor Analysis.

### Examples

``````data("stock611")
stock604 = stock611[-c(92,2,337,338,379,539,79), ]
data = as.matrix(stock604[, 3:12])

factors = 2
cor = TRUE
scoresMethod = "regression"

covx = rrcov::Cov(data)
covmat = list(cov = rrcov::getCov(covx), center = rrcov::getCenter(covx), n.obs = covx@n.obs)

out = stats::factanal(factors = factors, covmat = covmat)

out = computeScores(out, x = data, covmat = covmat, cor = cor, scoresMethod = scoresMethod)
out

``````

robustfa documentation built on April 16, 2023, 5:18 p.m.