DLFM (version 0.2.2)

DPC: Distributed principal component

Description

Distributed principal component

Usage

DPC(data, m, n1, K)

Value

Ahat,Dhat,Sigmahathat

Arguments

data

is a total data set

m

is the number of principal component

n1

is the length of each data subset

K

is the number of nodes

Examples

library(LaplacesDemon)
library(MASS)
n=1000
p=10
m=5
mu=t(matrix(rep(runif(p,0,1000),n),p,n))
mu0=as.matrix(runif(m,0))
sigma0=diag(runif(m,1))
F=matrix(mvrnorm(n,mu0,sigma0),nrow=n)
A=matrix(runif(p*m,-1,1),nrow=p)
lanor <- rlaplace(n*p,0,1)
epsilon=matrix(lanor,nrow=n)
D=diag(t(epsilon)%*%epsilon)
data=mu+F%*%t(A)+epsilon
DPC(data,m=3,n1=128,K=2)