Logit dynamics [Blume, Games and Economic Behavior, 1993] is a randomized best response dynamics where at every time step a player is selected uniformly at random and she chooses a new strategy according to the “logit choice function”, i.e. a probability distribution biased towards strategies promising higher payoffs, where the bias level corresponds to the degree of rationality of the agents. ...

Logit dynamics are a family of randomized best response dynamics based on the logit choice function [21] that is used to model players with limited rationality and knowledge. In this paper we study the all-logit dynamics, where at each time step all players concurrently update their strategies according to the logit choice function. In the well studied one-logit dynamics [7] instead at each ste...

The parameters of logit models are typically difficult to interpret, and the applied literature is replete with interpretive computational mistakes. In this article, I review a menu options interpret results logistic regressions correctly effectively using Stata. consider marginal effects, partial (contrasts of) predictive margins, elasticities, odds risk ratios. also show that interaction term...

Estimation of disaggregate mode choice models to estimate the ridership share on a proposed new (or improved) intercity travel service and to identify the modes from which existing intercity travelers will be diverted to the new or upgraded service constitutes a critical part of evaluating alternative travel service proposals to alleviate intercity travel congestion. This paper develops a new h...

Inspired by the interactive discrete choice logit models [Aggarwal, 2019], this paper presents the advanced families of discrete choice models, such as nested logit, mixed logit, and probit models to consider the interaction among the attributes. Besides the DM's attitudinal character is also taken into consideration in the computation of choice probabilities. The proposed choice models make us...

It is well understood that the two most popular empirical models of location choice conditional logit and Poisson return identical coefficient estimates when the regressors are not individual specific. We show that these two models differ starkly in terms of their implied predictions. The conditional logit model represents a zero-sum world, in which one region's gain is the other regions' loss....

The main feature of the CoIL challenge data is that the observed response is discrete: we only observe whether or not the customers buy caravan insurance. Models for such data were developed in the 1940s and 1950s in the Bio-statistics literature (see references in Cox and Snell, 1989), in particular LOGIT and PROBIT. In the 1970s such techniques became popular in Economics, where a utility max...