Extract sampling distributions from bootstrapped linear/loess models.
Extract sampling distributions from bootstrapped linear/loess models.
Extract sampling distributions of various entities from either a linear model or a loess bootstrap. Entities for linear models are currently, model coefficients, residual sum of squares, R-square, and fitted values (given a set of X values in the original bootstrap). For loess, one can extract residual sum of squares and fitted values.
samples(object, name = c("fitted","coef","rsquare","rss"))
Arguments
object: The output from either lm.boot or loess.boot.
name: The name of the entity to extract. The default is fitted values.
Returns
Either a vector or matrix depending on the entity extracted. For example, when extracting the sampling distributions for linear model coefficents, the return value is p x R matrix where p is the number of coefficients and R is the number of bootstrap replicates.
Examples
data(airquality)attach(airquality)lmodel <- lm(Ozone ~ Solar.R + Wind)lboot <- lm.boot(lmodel, R =100)## Get sampling distributions for coefficientss <- samples(lboot,"coef")## Histogram for the intercepthist(s[1,])