bootstrapSummary: Compare bootstrapping methods for linear regression...

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

Description

Compare bootstrapping methods for linear regression coefficients using summary statistics.

Usage

bootstrapSummary(bootList, lmodObs, summaryStats = c("mean", "median",
  "Q1", "Q3", "var", "IQR", "se", "MSE"))

Arguments

bootList	A list containing the bootstrapped sampling distributions of linear regression coefficients. Each element in the list should contain a data frame obtained using one of the six supported bootstrapping methods of size B x (k+1) where k is the number of predictors in the model. Column i of the data frame will be a sample of size B from the sampling distribution of β_{i}.
lmodObs	The observed linear model estimated by least squares. A fitted model object of class inheriting from 'lm'.
summaryStats	A string or a vector of strings. The desired summary statistics of the sampling of regression coefficients for the function to return. Options are: mean, median, Q1, Q3, IQR, var, se, and MSE.

Details

This function compares the summary statistics of bootstrapped sampling distributions for linear regression coefficients obtained in each of six methods: case resampling, residual resampling, Wild bootstrap with Mammen's Two-Point Distribution, Wild bootstrap with Mammen's Continuous Distribution, Wild boostrap with Rademacher Distribution, and Wild bootstrap with Standard Normal Distribution.

Author(s)

Natalie DelRocco

Examples

library(faraway)
data(prostate)
lmod <- lm(lpsa ~ lcavol + age + lweight, prostate)
bootsamps <- bootstrapSamples(lmodObs=lmod, formula='lpsa ~ lcavol + age + lweight',
                              data=prostate, B=1000)
bootstrapSummary(bootList = bootsamps, lmodObs = lmod,
                 summaryStats = c('median', 'var', 'se', 'IQR'))

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