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A Multinomial Extension of the Linear Logit Model
International Economic Review, 1969A large number of analyses in the social sciences are concerned with the determinants of the probability that a particular event will occur. For example, one may be interested in the forces which motivate commuters to use their cars to go to work as against some form of mass transport. Time, cost, and other considerations will play a role. Let p be the
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A multilevel multinomial logit model for the analysis of graduates’ skills
Statistical Methods and Applications, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
GRILLI, LEONARDO, RAMPICHINI, CARLA
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Preferences-based learning of multinomial logit model
Knowledge and Information Systems, 2018We learn the parameters of the popular multinomial logit model to gain insights about a DM’s decision process. We accomplish this objective through the recent algorithmic advances in the emerging field of preference learning. The empirical evaluation of the proposed approach is performed on a set of 12 publicly available benchmark datasets.
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Standard errors in the multinomial logit model
Communications in Statistics - Theory and Methods, 1986Asymptotic stmdard errors in the multinomial log it model are derived for efficient estimates of (A) the probability of choosing an alternative , (B) the change in the probability of choosing an alternative given a change in an explanatory variable , (C) the expected response, and (D) the change in the expected response given a change in an explanatory
Thomas B. Fomby, James E. Pearce
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The K-deformed multinomial logit model
Economics Letters, 2005Abstract We extend choice models where the deterministic part of the utility is subject to a deformation filter that affects how the choice probabilities react to changes in explanatory variables. We focus on extending the multinomial logit. Other generalizations are considered.
Rajaonarison, Dominique +2 more
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The Multinomial, Multiattribute Logit Choice Model
Journal of Marketing Research, 1979The authors argue that for the cross-sectional multiattribute approach to choice modeling, the multinomial logit is theoretically and empirically superior to the more commonly used regression approach. Other choice methodologies also are discussed briefly in relation to logit.
Dennis H. Gensch, Wilfred W. Recker
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The Nested Multinomial Logit Model
1987An important and intuitive generalization of the MNL specification is the nested multinomial logit (NMNL) model (McFadden, 1978). This model is able to generate substantial deviations from the “Independence of Irrelevant Alternatives” assumption but retains most of the computational advantages of the MNL model. Because of these features, the NMNL model
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Approximate inference for the multinomial logit model
Statistics & Probability Letters, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Testing for IIA in the Multinomial Logit Model
Sociological Methods & Research, 2007The multinomial logit model is perhaps the most commonly used regression model for nominal outcomes in the social sciences. A concern raised by many researchers, however, is the assumption of the independence of irrelevant alternatives (IIA) that is implicit in the model.
Simon Cheng, J. Scott Long
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Pooling states in the multinomial logit model
Journal of Econometrics, 1991The distinction of separate states in a multinomial logit model can be tested by a likelihood ratio test that is easy to apply.
CRAMER, JS, RIDDER, G
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