primePCA (version 1.2)

inverse_prob_method: Inverse probability weighted method for estimating the top K eigenspaces

Description

Inverse probability weighted method for estimating the top K eigenspaces

Usage

inverse_prob_method(X, K, trace.it = F, center = T, normalize = F)

Arguments

X

a numeric matrix with \(NA\)s or "Incomplete" matrix object (see softImpute package)

K

the number of principal components of interest

trace.it

report the progress if trace.it == TRUE

center

center each column of X if center == TRUE. The default value is TRUE.

normalize

normalize each column of X such that its sample variance is 1 if normalize == TRUE. The default value is False.

Value

Columnwise centered matrix of the same dimension as \(X\).

Examples

# NOT RUN {
X <- matrix(1:30 + .1 * rnorm(30), 10, 3)
X[1, 1] <- NA
X[2, 3] <- NA
v_hat <- inverse_prob_method(X, 1)
# }