bootCases: Empirical boostrap for linear regression coefficients

In ndelrocco/lmBootCompare: Compares Six Methods of Bootstrapping Linear Model Coefficients

Description

Empirical boostrap for linear regression coefficients (Description)

Usage

bootCases(formula, data, B)

Arguments

formula	A string that can be coerced into class 'formula'. Usually of the form response variable \sim predictor variables.A symbolic description of the model to be fitted.
data	data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model.
B	The number of bootstrap replicates. Usually this will be a single positive integer.

Details

This function simulates the sampling distribution of simple linear regression coefficients by first simulating the joint distribution of (\mathbf{X},Y) by the empirical distribution function of the cases (i.e. resampling cases with replacement).

Value

A B x (k+1) data frame containing B samples from the distributions of each of the (k+1) model parameters, where k is the number of predictors in the model.

Author(s)

Natalie DelRocco

References

Davison, A.C. and Hinkley, D.V. (1997) Bootstrap Methods and Their Application. Cambridge University Press.

Examples

library(faraway)
data(prostate)
bootsamps <- bootCases(formula='lpsa ~ lcavol + age + lweight', data=prostate, B=1000)

ndelrocco/lmBootCompare documentation built on Dec. 10, 2019, 12:38 p.m.