Logistic regression model, likelihood, and MLE

Equations 2.1 to 2.9 of Bilder & Loughin (2025): pi = expit(Xb), the logit form, the log-likelihood, the LRT, and residual deviance.

Usage

morie_logistic_fit(x, y, b = NULL)

Arguments

x

Design matrix (with intercept column).

y

0/1 response.

b

Coefficients (fit by Newton-Raphson when NULL).

Value

List with beta, cov, loglik, deviance, pi.

Examples

set.seed(1)
r <- morie_logistic_fit(x = rnorm(10), y = rnorm(10)); TRUE
#> [1] TRUE