svd_mis: A svd algorithm with the option for missing values

In YipengUva/RpESCA: R implementaion of pESCA models with various concave penalties

Description

This function implemented a MM algorithm to fit a svd on a quantitaive data set with missing values. The details of this function can be found in https://arxiv.org/abs/1902.06241.

Usage

svd_mis(X, R, opts = list())

Arguments

X	a quantitative data set
R	the number of PCs
opts	a list contains the setting for the algorithm. tol_obj: tolerance for relative change of hist_obj, default:1E-6; maxit: max number of iterations, default: 1000;

Value

This function returns a list contains

• U: the left singular vectors

• S: the diagnal matrix contains the singular values

• V: the right singular vectors

• iter: the number of iterations used

• cvErrors: K-fold cross validation errors

• diagnose: records hist_obj and rel_obj

Examples

## Not run: svd_mis(X,R = 3,opts=list())

YipengUva/RpESCA documentation built on July 2, 2019, 6:41 p.m.