DSFM (version 1.0.1)

DGaoPC: Distributed Gao Principal Component Analysis

Description

Performs distributed Gao-type principal component analysis on a numeric dataset split across multiple nodes.

Usage

DGaoPC(data, m, n1, K)

Value

A list with the following components:

AG1

List of estimated loading matrices for the first-stage components for each node.

AG2

List of estimated loading matrices for the second-stage components for each node.

DG3

List of diagonal residual variance matrices for each node.

sGhat

List of covariance matrices of reconstructed data for each node.

Arguments

data

A numeric matrix containing the total dataset.

m

An integer specifying the number of principal components for the first stage.

n1

An integer specifying the length of each data subset.

K

An integer specifying the number of nodes.

Examples

set.seed(123)
data <- matrix(rnorm(500), nrow = 100, ncol = 5)
DGaoPC(data = data, m = 3, n1 = 20, K = 5)