We compare multinomial logit and mixed logit models for data on California households’ revealed and stated preferences for automobiles. The stated preference data elicited households’ preferences among gas, electric, methanol, and CNG vehicles with various attributes. The mixed logit models provide a much better fit to these data, and forecasting exercises demonstrate substantial differences be...

This chapter examines different models commonly used to model probabilistic choice, such as eg the choice of one type of transportation from among many choices available to the consumer. Section 1 discusses derivation and limitations of conditional logit models. Section 2 discusses probit models and Section 3 discusses the nested logit (generalized extreme value models), which address some of t...

There is a strong competition from low-priced imported catfish fillets resulting in a declining market share for domestic farm-raised catfish fillets. To match the competition, catfish processors are embarking on pricing policy measures that are volume-oriented instead of profitor image-oriented. This could be an effective short-run pricing policy measure for optimal longrun sustainability and ...

Predicting business failure of listed companies is a hot topic because of the emergency of financial crisis in developed countries recently. The two classical statistical methods of multivariate discriminant analysis (MDA) and logistic regression (logit) have taken a key role in the area of business failure prediction (BFP). However, they are frequently criticized for the relative low predictiv...

Logit kernel is a discrete choice model that has both probit-like disturbances as well as an additive i.i.d. extreme value (or Gumbel) disturbance à la multinomial logit. The result is an intuitive, practical, and powerful model that combines the flexibility of probit with the tractability of logit. For this reason, logit kernel has been deemed the “model of the future” and is becoming extremel...

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models...

Elimination by aspects (EBA) is a random utility model that is considered to represent the choice process used by consumers more faithfully than logit and probit models. One limitation of the model is that it does not have a known error theory. We show that EBA can be derived by assuming that aspects have random utilities with independent, extreme value distributions. Multinomial logit and rank...

In this study we assess the ability of the Marine Recreational Fishery Statistics Survey (MRFSS) to support single-species recreation demand models. We use the 2000 MRFSS southeast intercept data combined with the economic add-on. We determine that the MRFSS data will support only a few species-specific recreation demand models. Considering species of management interest in the southeast, we fo...

In this paper, we develop improved techniques for defending against adversarial examples at scale. First, we implement the state of the art version of adversarial training at unprecedented scale on ImageNet and investigate whether it remains effective in this setting—an important open scientific question (Athalye et al., 2018). Next, we introduce enhanced defenses using a technique we call logi...