In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models ...

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...

For cross-classification tables having an ordinal response variable, logit and probit models are formulated for the probability that a pair of subjects is concordant. For multidimensional tables, generalized models are given for the probability that the response at one setting of explanatory variables exceeds the response at another setting. Related measures of association are discussed for two...

We show that the distributions of random coefficients in various discrete choice models are nonparametrically identified. Our identification results apply to static discrete choice models including binary logit, multinomial logit, nested logit, and probit models as well as to dynamic programming discrete choice models. In these models the only key condition we need to verify for identification ...

A Bayesian probit model with individual effects that exhibit spatial dependencies is set forth. Since probit models are often used to explain variation in individual choices, these models may well exhibit spatial interaction effects due to the varying spatial location of the decision makers. That is, individuals located at similar points in space may tend to exhibit similar choice behavior. The...

To treat with social phenomena, statistical and mathematical physics provides a powerful and rigorous method [1], and several papers have studied the models of social phenomena based on stochastic processes. Many researchers in econometrics or biometrics have proposed that the discrete choice including binary analysis may be formulated as the AR (autoregressive), logit, and probit models [2]. I...