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. ...

Balance-sheet data offer a potentially large number of candidate predictors of corporate financial failure. In this paper we provide a novel predictor selection procedure based on non-parametric regression and classification tree method (CART) and test its performance within a standard logit model. We show that a simple logit model with dummy variables created in accordance with the nodes of es...

This paper uses data on automobile purchases to compare two alternatives to the multinomial logit model. The results indicate that the nested logit model is likely to be superior to the more general Berry–Levinsohn–Pakes model for applications using aggregate-level data.  2000 Elsevier Science S.A. All rights reserved.

A major drawback associated with the use of classical statistical methods for business failure prediction on top of financial distress is their lack of high accuracy rate. This work analyses the use of the two-stage ensemble of multivariate discriminant analysis (MDA) and logit to improve predictive performance of classical statistical methods. All possible ratios are firstly built from the qua...

health and safety are important factors in today’s life. most of studies show that consuming the chicken that has anti biotic caused different diseases like digestive vessel cancer. attention to controlled use of antibiotics can play a key role in society health which considered in the production of green chicken. planning for increasing the production of mentioned chicken needs the investigati...

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...

In this paper, we study optimal model averaging estimators of regression coefficients in a multinomial logit model, which is commonly used many scientific fields. A Kullback–Leibler (KL) loss-based weight choice criterion developed to determine weights. Under some regularity conditions, prove that the resulting are asymptotically optimal. When true one candidate models, averaged consistent. Sim...