OPC: Apply the OPC method to the Laplace factor model

In LFM: Laplace Factor Model Analysis and Evaluation

Apply the OPC method to the Laplace factor model

Description

This function computes Online Principal Component Analysis (OPC) for the provided input data, estimating factor loadings and uniquenesses. It calculates mean squared errors and sparsity for the estimated values compared to true values.

Usage

OPC(data, m, eta)

Arguments

data	is a highly correlated online data set
m	is the number of principal component
eta	is the proportion of online data to total data

Value

Ao,Do

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
results <- OPC(data, m, eta=0.1)
print(results)

LFM documentation built on Dec. 6, 2025, 5:06 p.m.