FPCdpca (version 0.1.0)

Drsvd: Distributed random svd

Description

Distributed random svd is a technology that applies random SVD to distributed computing environments.

Usage

Drsvd(data,K, nk,m,q,k)

Value

MSEXrsvd

The MSE value of Xrsvd

MSEvrsvd

The MSE value of vrsvd

MSESrsvd

The MSE value of Srsvd

kopt

The size of optimal subset

Arguments

data

sparse random projection matrix.

K

the number of distributed nodes.

nk

the size of subsets.

m

the dimension of variables.

q

number of additional power iterations.

k

the desired target rank.

Examples

K=20; nk=50; nr=10; p=8; m=5; q=5;k=4;n=K*nk;
data=X=matrix(rexp(n*p,0.8),ncol=p)
#data=matrix(c(rnorm((n-nr)*p,0,1),rpois(nr*p,100)),ncol=p)
#data=X=matrix(rpois((n-nr)*p,1),ncol=p); rexp(nr*p,1); rchisq(10000, df = 5);
#data=X=matrix(rexp(n*p,0.8),ncol=p)
Drsvd(data=data,K=K,nk=nk,m=m,q=q,k=k)