<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Random Utility Models | José Ángel Martín Baos</title><link>https://joseangelmartin.com/es/tags/random-utility-models/</link><atom:link href="https://joseangelmartin.com/es/tags/random-utility-models/index.xml" rel="self" type="application/rss+xml"/><description>Random Utility Models</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>es-es</language><lastBuildDate>Fri, 07 Feb 2025 00:00:00 +0000</lastBuildDate><image><url>https://joseangelmartin.com/media/icon_hu_e1d52914376ca381.png</url><title>Random Utility Models</title><link>https://joseangelmartin.com/es/tags/random-utility-models/</link></image><item><title>Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling</title><link>https://joseangelmartin.com/es/publication/mgr-25/</link><pubDate>Fri, 07 Feb 2025 00:00:00 +0000</pubDate><guid>https://joseangelmartin.com/es/publication/mgr-25/</guid><description/></item><item><title>A prediction and behavioural analysis of machine learning methods for modelling travel mode choice</title><link>https://joseangelmartin.com/es/publication/mlr-23/</link><pubDate>Wed, 01 Nov 2023 00:00:00 +0000</pubDate><guid>https://joseangelmartin.com/es/publication/mlr-23/</guid><description/></item><item><title>A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression</title><link>https://joseangelmartin.com/es/publication/mgr-21-b/</link><pubDate>Wed, 08 Dec 2021 00:00:00 +0000</pubDate><guid>https://joseangelmartin.com/es/publication/mgr-21-b/</guid><description/></item></channel></rss>