cp_BIC | R Documentation |
Computes bayesian information criterion for comparing competing models.
cp_BIC(ll, n, k)
ll |
numeric vector of length 1 (or an object of class 'logLik') storing the log-likelihood of the model of interest |
n |
numeric vector of length 1 storing the sample size of data used to compute the log-likelihood |
k |
numeric vector of length 1 storing the number of estimated parameters by the model |
numeric vector of length 1 storing the computed BIC.
Edoardo Costantini, 2023
# Fit some model
lm_out <- lm(mpg ~ cyl + disp, data = mtcars)
# Compute BIC with your function
BIC_M <- cp_BIC(
ll = logLik(lm_out),
n = nobs(lm_out),
k = length(coef(lm_out)) + 1 # intercept + reg coefs + error variance
)
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