samples function

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 coefficients s <- samples(lboot, "coef") ## Histogram for the intercept hist(s[1,])

Author(s)

Roger D. Peng