residuals.lm.spike: Extract lm.spike Residuals

In BoomSpikeSlab: MCMC for Spike and Slab Regression

Extract lm.spike Residuals

Description

Get residuals from an lm.spike object.

Usage

## S3 method for class 'lm.spike'
residuals(
    object,
    burn = SuggestBurnLogLikelihood(object$log.likelihood),
    mean.only = FALSE,
    ...)

Arguments

object	An object of class lm.spike.
burn	The number of MCMC iterations in the object to be discarded as burn-in.
mean.only	Logical. If TRUE then the posterior mean of each residual is returned. If FALSE then the full posterior distribution of residuals is returned.
...	Unused, but present for compatibility with generic residuals function.

Value

The posterior distribution (or posterior mean) of residuals from the model object. If mean.only is TRUE then the return value is the vector of residuals, otherwise the return value is a matrix, with rows corresponding to MCMC iterations, and columns to individual observations.

Author(s)

Steven L. Scott

See Also

lm.spike SpikeSlabPrior summary.lm.spike plot.lm.spike

Examples

  niter <- 1000
  n <- 100
  p <- 10
  ngood <- 3

  x <- cbind(1, matrix(rnorm(n * (p-1)), nrow=n))
  beta <- rep(0, p)
  good <- sample(1:p, ngood)
  beta[good] <- rnorm(ngood)
  sigma <- 1

  y <- rnorm(n, x %*% beta, sigma)
  model <- lm.spike(y ~ x - 1, niter=niter)
  plot(model)
  residuals(model)
  residuals(model, mean.only = TRUE)

BoomSpikeSlab documentation built on May 29, 2024, 5:07 a.m.