Results 51 to 60 of about 64,895 (200)
Using Clustering Methods in Multinomial Logit Model for Departure Time Choice
Journal of Advanced Transportation, 2020 Travellers have to make some decisions for each trip, and one of them is the choice of departure time. Discrete choice models have been employed as an approach to departure time modelling by many researchers.
Shahriar Afandizadeh Zargari +1 more
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A very brief survey of regression for categorical data. Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of two or more categories an outcome of interest ...
A. Colin Cameron
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Optimizing Expected Utility in a Multinomial Logit Model with Position Bias and Social Influence [PDF]
, 2014 Motivated by applications in retail, online advertising, and cultural markets, this paper studies how to find the optimal assortment and positioning of products subject to a capacity constraint. We prove that the optimal assortment and positioning can be
Abeliuk, Andres +3 more
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Dirichlet-Multinomial Regression [PDF]
In this paper we provide a Random-Utility based derivation of the Dirichlet-Multinomial regression and posit it as a convenient alternative for dealing with overdispersed multinomial data.
Paulo Guimaraes, Richard Lindrooth
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Risk Perceptions and Risk Management Strategies in French Oyster Farming [PDF]
The article analyses risk perception in shellfish farming as well as farmers' willingness to rely on coverage mechanisms. Factor and econometric analyses (logit and ordered multinomial logit models) have shown that a number of socio-economic factors ...
Patrice Guillotreau +2 more
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Context-aware Bayesian mixed multinomial logit model
Journal of Choice ModellingThe mixed multinomial logit model assumes constant preference parameters of a decision-maker throughout different choice situations, which may be considered too strong for certain choice modelling applications. This paper proposes an effective approach to model context-dependent intra-respondent heterogeneity, thereby introducing the concept of the ...
Mirosława Łukawska +2 more
openaire +3 more sources
Comparing discrete choice and machine learning models in predicting destination choice
European Transport Research ReviewDestination choice modeling has long been dominated by theory-based discrete choice models. Simultaneously, machine learning has demonstrated improved predictive performance to other fields of discrete choice modeling.
Ilona Rahnasto, Martijn Hollestelle
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Some aspects of random utility, extreme value theory and multinomial logit models [PDF]
In this paper we give a survey on some basic ideas related to random utility, extreme value theory and multinomial logit models. These ideas are well known within the field of spatial economics, but do not appear to be common knowledge to researchers in ...
Andersson, Jonas, Ubøe, Jan
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Factors affecting packed and unpacked fluid milk consumption
Agricultural Economics (AGRICECON), 2009 This article identifies consumer characteristics associated with preferences toward fluid milk alternatives. Using consumer survey data from Samsun province of Turkey and Multinomial Logit model, unpacked and packed fluid milk preferences were analyzed ...
O. Kilic, C. Akbay, G. Yildiz Tiryaki
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Visualization of Categorical Response Models - from Data Glyphs to Parameter Glyphs [PDF]
, 2012 The multinomial logit model is the most widely used model for nominal multi-category responses. One problem with the model is that many parameters are involved, another that interpretation of parameters is much harder than for linear models because the ...
Schauberger, Gunther, Tutz, Gerhard
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