Discriminating Methods: Tests for Non-Nested Discrete Choice Models

Discrete Choice Models for Non-Intrusive Quality Assessment

Non-intrusive signal quality assessment in general, and its application to speech signal processing, in particular, builds extensively upon statistical regression models. Commonly, the raw preference scores used for fitting these models belong to a categorical scale. Averaging the scores over a number of test subjects results in smooth, close-to-continuous ratings, thus justifying the use of re...

Data Models for Discrete Choice

Social Discrete Choice Models

Human decision making underlies data generating process in multiple application areas, and models explaining and predicting choices made by individuals are in high demand. Discrete choice models are widely studied in economics and computational social sciences. As digital social networking facilitates information flow and spread of influence between individuals, new advances in modeling are nee...

Discrete Choice Models

Discrete choice models are employed (as the name suggests) to explain a discrete choice that an individual makes. For example, such a choice might be whether or not to join the labor force, whether or not to buy a car, whether or not to continue on to graduate school, whether or not to accept a job with a consulting …rm, or whether or not to sign up with an internet provider. Later in the cours...

Discrete choice models

Discrete choice models have played an important role in transportation modeling for the last 25 years. They are namely used to provide a detailed representation of the complex aspects of transportation demand, based on strong theoretical justiications. Moreover, several packages and tools are available to help practionners using these models for real applications, making discrete choice models ...