plot.MHLS: Plot Metropolis-Hastings sampler outputs

In EAlasso: Simulation Based Inference of Lasso Estimator

Description

Provides six plots for each covariate index; histogram, path plot and acf plot for beta and for its subgradient.

Usage

## S3 method for class 'MHLS'
plot(x, index = 1:ncol(x$beta), skipS = FALSE, ...)

Arguments

x	an object of class "MHLS", which is an output of MHLS.
index	an index of covariates to plot.
skipS	logical. If skipS = TRUE, plots beta only.
...	addtional arguments passed to or from other methods.

Details

plot.MHLS provides summary plots of beta and subgradient. The first column provides histogram of beta and subgradient, while the second and the third columns provide path and acf plots, respectively. If skipS = TRUE, this function provides summary plots for beta only.

Examples

#' set.seed(123)
n <- 10
p <- 5
X <- matrix(rnorm(n * p), n)
Y <- X %*% rep(1, p) + rnorm(n)
sigma2 <- 1
lbd <- .37
weights <- rep(1, p)
LassoResult <- Lasso.MHLS(X = X, Y = Y, lbd = lbd, type="lasso", weights = weights)
B0 <- LassoResult$B0
S0 <- LassoResult$S0
plot(MHLS(X = X, PE = rep(0, p), sig2 = 1, lbd = 1, group = 1:p,
     weights = weights, B0 = B0, S0 = S0, niter = 50, burnin = 0,
     type = "coeff"))

EAlasso documentation built on Sept. 1, 2017, 9:03 a.m.