Depca {FPCdpca}

Decentralized PCA

Description

Decentralized PCA is a technology that applies decentralized PCA to distributed computing environments.

Usage

Depca(data,K,nk, eps,nit.max)

Arguments

data

is sparse random projection matrix.

K

is the desired target rank.

nk

is the size of subsets.

eps

is the noise.

nit.max

is the repeat times.

Value

MSEXrp,MSEvrp, MSESrp, kopt

Examples

K=20; nk=50; nr=10; p=8; k=4; n=K*nk;d=6
data=matrix(c(rnorm((n-nr)*p,0,1),rpois(nr*p,100)),ncol=p)
set.seed(1234)
eps=10^(-1);nit.max=1000
TXde=TSde=c(rep(0,5))
for (j in 1:5){
  depca=Depca(data=data,K=K, nk=nk,eps=eps,nit.max=nit.max)
  TXde[j]=as.numeric(depca)[1]
  TSde[j]=as.numeric(depca)[2]
}
mean(TXde)
mean(TSde)