gam.nbut

This is an internal function of package <code>mgcv</code>. It is called by <code>gam()</code> 
for data where the error distribution is known to follow the Negative Binomial, but the 
value of theta is unknown. Based on <code>glm.nb()</code> from the MASS library, it calls
<code>gam.fit()</code> repeatedly while iteratively improving its estimate of
theta, starting from a poisson error model and uses the <code>neg.bin</code>
error family (based again on code from the MASS library).

models

regression

smooth

Routines for GAMs and other generalized ridge regression problems 
             with multiple smoothing parameter selection by GCV or UBRE.
             Includes an implementation (not a clone) of gam().

State of Data and AI Literacy Report 2025

gam.nbut: Generalized Additive Models using Negative Binomial errors with unknown theta

Description

Arguments

Value

See Also