Overview: Categorical Data and Graphics Methods for discrete distributions – testing goodness of fit Hanging rootograms Robust distribution plots Methods for two-way frequency tables – understanding association Fourfold displays Sieve diagrams Mosaic displays and loglinear models for n-way tables Mosaic displays Mosaic matrices Correspondence analysis and MCA Logistic and logit regression Logit...

Mixed logit is a highly flexible model that can approximate any random utility model. In this paper, two kinds of mixed multinomial logit models were considered. The main aim was to introduce a locally D-optimal criterion to obtain an optimal combination of the levels of attributes for producing alternatives and an optimal combination of alternatives in choice sets. Thus, a design including cho...

Many researchers have used the conditional logit model to examine migration. One common objection to this model is that it carries the independence from irrelevant alternatives (IIA) assumption, which may be too restrictive. This study compares the conditional logit with models that partially relax (nested logit) or fully relax (mixed logit) the IIA assumption. We will begin to learn whether as...

Network formation among individuals constitutes an important part of many OR processes, but relatively little is known about how individuals make their linking decisions in networks. This article provides an investigation of heuristic effects in individual linking decisions for network formation in an incentivized lab-experimental setting. Our mixed logit analysis demonstrates that the inherent...

Theory: The spatial model of elections can better be represented by using conditional logit than by multinomial logit. The spatial model, and random utility models in general, suffer from a failure to adequately consider the sub­ stitutability of candidates sharing similar or identical issue positions. Hypotheses: Multinomial logit is not much better than successive applications of binomial log...

This report formulates and applies a unified mixed-logit framework for joint analysis of revealed and stated preference data that accommodates a flexible competition pattern across alternatives, scale difference in the revealed and stated choice contexts, heterogeneity across individuals in the intrinsic preferences for alternatives, heterogeneity across individuals in the responsiveness to lev...

Previous works have extensively studied the transferability of adversarial samples in untargeted black-box scenarios. However, it still remains challenging to craft targeted examples with higher than non-targeted ones. Recent studies reveal that traditional Cross-Entropy (CE) loss function is insufficient learn transferable due issue vanishing gradient. In this work, we provide a comprehensive ...