HighDim {SPSP}

A high dimensional dataset with n equals to 200 and p equals to 500.

Description

A dataset with 200 observations and 500 dimensions is generated from the following process: linear regression model with only first three non-zero coefficients equal to 3, 2, and 1.5 respectively. The covariates are correlated with AR structure (rho=0.3). The error term is normally distributed with zero mean and sd equals to 0.5.

Usage

data(HighDim)

Examples

# HighDim dataset is generated from the following process:
n <- 200; p <- 500; sigma <- 0.5
beta <- rep(0, p); nonzero <- c(1, 2, 3); zero <- setdiff(1:p, nonzero)
beta[nonzero] <- c(3, 2, 1.5)
Sigma <- 0.3^(abs(outer(1:p,1:p,"-")))
library(MASS)
X <- mvrnorm(n, rep(0,p), Sigma)
error <- rnorm(n, 0, sigma)

X <- apply(X, 2, scale) * sqrt(n)/sqrt(n-1)
error <- error - mean(error)

Y <- X %*% beta + error
HighDim <- data.frame(Y, X)
head(HighDim)