cv_ZIPFA: Cross validation for Zero Inflated Poisson factor analysis

In ZIPFA: Zero Inflated Poisson Factor Analysis

Description

To conduct a cross validation for Zero Inflated Poisson factor analysis to find the number of factors.

Usage

cv_ZIPFA(X, k, fold, tau = 0.1, cut = 0.8, tolLnlikelihood = 5e-4,
          iter = 20, tol = 1e-4, maxiter = 100, initialtau = 'iteration',
          Madj = TRUE, display = TRUE, parallel = FALSE)

Arguments

X	The matrix to be decomposed.
k	A vector containing the number of factors to try.
fold	The number of folds used in cross validation.
tau	Initial tau value to fit. Will be overwritten by the first value in initial argument.
cut	To delete columns that has more than 100('Cut')% zeros. Cut = 1, if no filtering.
tolLnlikelihood	The max percentage of log likelihood differences in two iterations.
iter	Max iterations.
initialtau	A character specifying the way to choose the initial value of tau at the beginning of EM iteration. stable: estimate tau from fitted beta in last round; initial: always use the initially assigned tau in tau or initial. Use the default tau = 0.1 if 'initial' is empty. iteration: use fitted tau in last round.
tol	Percentage of l2 norm change of [tau beta].
maxiter	Max iteration number in the zero inflated poisson regression.
Madj	If TRUE then adjust for relative library size M.
display	If TRUE display the fitting procedure.
parallel	Use doParallel and foreach package to accelerate.

Details

The function conducts cross validation on the zero-inflated Poisson factor analysis to determine the rank.

Value

The function returns a matrix. Each row the CV likelihood of one fold. Each column is the result of number of factors in k.

Author(s)

Tianchen Xu

Examples

data(X)
cv_ZIPFA(X, fold = 10, k = c(3,4))

ZIPFA documentation built on April 1, 2020, 1:07 a.m.