lm.beta.boot.conf: Bootstrapped Confidence Functions for Coefficients of a...
In ddarmon/clp: R Package for Computing Confidence Functions to Accompany CLP
Description
Usage
Arguments
Value
References
Examples
Description
Bootstrapped confidence functions for coefficients of a linear model
using BCa and the case resampling bootstrap.
Usage
1
lm.beta.boot.conf(formula, data, B = 2000)
Arguments
formula
the model to be fitted
data
the data frame containing the data for fitting
B
the number of bootstrap samples used to approximate the
bootstrap distribution
Value
A list of lists containing the confidence functions pconf, dconf, cconf, and qconf
for each coefficient of the linear model, as well as
the P-curve and S-curve.
References
Tore Schweder and Nils Lid Hjort. Confidence, likelihood, probability. Vol. 41. Cambridge University Press, 2016.
Bradley Efron and Trevor Hastie. Computer Age Statistical Inference. Vol. 5. Cambridge University Press, 2016.
Examples
1
2
3
4
5
data(fat)
beta.boot.conf <- lm.beta.boot.conf(body.fat ~ age + weight + height, data = fat, B = 2000)
display.cconf(beta.boot.conf$weight)
ddarmon/clp documentation built on Jan. 25, 2021, 6:22 p.m.
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Description Usage Arguments Value References Examples
Description
Bootstrapped confidence functions for coefficients of a linear model using BCa and the case resampling bootstrap.
Usage
1 | lm.beta.boot.conf(formula, data, B = 2000)
|
Arguments
formula |
the model to be fitted |
data |
the data frame containing the data for fitting |
B |
the number of bootstrap samples used to approximate the bootstrap distribution |
Value
A list of lists containing the confidence functions pconf, dconf, cconf, and qconf for each coefficient of the linear model, as well as the P-curve and S-curve.
References
Tore Schweder and Nils Lid Hjort. Confidence, likelihood, probability. Vol. 41. Cambridge University Press, 2016.
Bradley Efron and Trevor Hastie. Computer Age Statistical Inference. Vol. 5. Cambridge University Press, 2016.
Examples
1 2 3 4 5 | data(fat)
beta.boot.conf <- lm.beta.boot.conf(body.fat ~ age + weight + height, data = fat, B = 2000)
display.cconf(beta.boot.conf$weight)
|
R Package Documentation
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