log_likelihood function

Calculate the negative log-likelihood for a beta binomial regression model

This function computes the negative log-likelihood for a beta binomial regression model where both the mean and standard deviation are modeled as functions of predictors.

log_likelihood(params, X, Z, y, weights)

Arguments

• params: A numeric vector containing all model parameters. The first n_beta elements are coefficients for the mean model, and the remaining elements are coefficients for the log-standard deviation model.
• X: A matrix of predictors for the mean model.
• Z: A matrix of predictors for the log-standard deviation model.
• y: A numeric vector of response values.
• weights: A numeric vector of weights for each observation.

Returns

The negative log-likelihood of the model.