residuals.lm.spike | R Documentation |
Get residuals from an lm.spike
object.
## S3 method for class 'lm.spike' residuals( object, burn = SuggestBurnLogLikelihood(object$log.likelihood), mean.only = FALSE, ...)
object |
An object of class |
burn |
The number of MCMC iterations in the object to be discarded as burn-in. |
mean.only |
Logical. If |
... |
Unused, but present for compatibility with generic
|
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.
Steven L. Scott
lm.spike
SpikeSlabPrior
summary.lm.spike
plot.lm.spike
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)
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