AlternateSVD: Alternating singular value decomposition

Description Usage Arguments Value Author(s)

View source: R/leapp.R

Description

The algorithm alternates between 1) computing latent loadings u and latent variable v and 2) estimating noise standard deviation for each of the N genes.

Usage

1
AlternateSVD(x, r, pred = NULL, max.iter = 10, TOL = 1e-04)

Arguments

x

an N by n data matrix

r

a numeric, number of latent factors to estimate

pred

an n by s matrix, each column is a vector of known covariates for n samples, s covariates are considered, default to NULL

max.iter

a numeric, maximum number of iteration allowed, default to 10

TOL

a numeric, tolerance level for the algorithm to converge, default to 1e-04

Value

sigma

a vector of length N, noise standard deviations for N genes

coef

an N by s matrix, estimated coefficients for known covariates

uest

an N by r matrix, estimated latent loadings

vest

an n by r matrix, estiamted latent factors

Author(s)

Yunting Sun yunting.sun@gmail.com, Nancy R.Zhang nzhang@stanford.edu, Art B.Owen owen@stanford.edu


leapp documentation built on May 2, 2019, 2:12 p.m.