n-Raphson methods or backfitting algorithms (e.g., Algorithm 9.1 - 9.2 in the text) for GAM. When all the variables <span class="arithmatex">\(X_k\)</span> are discrete (e.g., survey response data), it reduces to the so-called <em>linear multinomial choice model</em> and parameters can be fit by maximizing the conditional log-likelihood (<a href="https://mitpress.mit.edu/books/discrete-choice-analysis">Discrete choice analysis: theory and application to travel demand</a>).</p>
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