lm.beta.conf: Confidence Functions for the Coefficients of a Linear Model
In ddarmon/clp: R Package for Computing Confidence Functions to Accompany CLP
Description
Usage
Arguments
Value
References
Examples
Description
Confidence functions for the coefficients of a linear model under
Gaussian noise assumptions.
Usage
1
lm.beta.conf(mod)
Arguments
mod
an output from lm
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.
Examples
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9
# Prediction of body fat percentage from other body measurements.
data(fat)
mod <- lm(body.fat ~ age + weight + height, data = fat)
beta.conf <- lm.beta.conf(mod)
display.cconf(beta.conf$weight)
ddarmon/clp documentation built on Jan. 25, 2021, 6:22 p.m.
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Description Usage Arguments Value References Examples
Description
Confidence functions for the coefficients of a linear model under Gaussian noise assumptions.
Usage
1 | lm.beta.conf(mod)
|
Arguments
mod |
an output from lm |
Value
A list of lists containing the confidence functions pconf, dconf, cconf, and qconf for each coefficient of the linear model, as well as the P-curve and S-curve.
References
Tore Schweder and Nils Lid Hjort. Confidence, likelihood, probability. Vol. 41. Cambridge University Press, 2016.
Examples
1 2 3 4 5 6 7 8 9 | # Prediction of body fat percentage from other body measurements.
data(fat)
mod <- lm(body.fat ~ age + weight + height, data = fat)
beta.conf <- lm.beta.conf(mod)
display.cconf(beta.conf$weight)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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