Description Usage Arguments Value Examples
Calculate the -2 * log likelihood of a dataset given a specified model.
1 | loglikelihood(b, dataset)
|
b |
intercept and coefficients of a generalized linear model. |
dataset |
a test dataset used to derive the likelihood. |
the function returns the -2 * log likelihood.
1 2 3 4 5 6 7 8 | ## Using the mtcars dataset
## Resample, fit an ordinary least squares model and calculate likelihood
data(mtcars)
mtc.data <- cbind(1,datashape(mtcars, y = 8, x = c(1, 6, 9)))
head(mtc.data)
mtc.boot <- randboot(mtc.data, replace = TRUE)
boot.betas <- ml.rgr(mtc.boot)
loglikelihood(b = boot.betas, dataset = mtc.data)
|
mpg wt am vs
[1,] 1 21.0 2.620 1 0
[2,] 1 21.0 2.875 1 0
[3,] 1 22.8 2.320 1 1
[4,] 1 21.4 3.215 0 1
[5,] 1 18.7 3.440 0 0
[6,] 1 18.1 3.460 0 1
[,1]
[1,] 23.66545
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