factor_analysis {anomalyDetection} | R Documentation |
factor_analysis
reduces the structure of the data by relating the
correlation between variables to a set of factors, using the eigen-decomposition
of the correlation matrix.
factor_analysis(data, hc_points)
data |
numeric data |
hc_points |
vector of eigenvalues [designed to use output from |
A list containing:
fa_loadings
: numerical matrix with the original factor loadings
fa_scores
: numerical matrix with the row scores for each factor
fa_loadings_rotated
: numerical matrix with the varimax rotated factor loadings
fa_scores_rotated
: numerical matrix with the row scores for each varimax rotated factor
num_factors
: numeric vector identifying the number of factors
H. F. Kaiser, "The Application of Electronic Computers to Factor Analysis," Educational and Psychological Measurement, 1960.
horns_curve
for computing the average eigenvalues used for hc_points
argument
# Perform Factor Analysis with matrix \code{x} x <- matrix(rnorm(200*3), ncol = 10) x %>% horns_curve() %>% factor_analysis(x, hc_points = .)