The so-called “mixed” or “heterogeneous” multinomial logit (MIXL) model has become popular in a number of fields, especially Marketing, Health Economics and Industrial Organization. In most applications of the model, the vector of consumer utility weights on product attributes is assumed to have a multivariate normal (MVN) distribution in the population. Thus, some consumers care more about som...

backgrounds and aims: the tehran province was subject to the second highest incidence of fatalities due to traffic accidents in 1390. most studies in this field examine rural traffic accidents, but this study is based on the use of logit models and artificial neural networks to evaluate the factors that affect the severity of accidents within the city of tehran. materials and methods: among the...

We introduce a new nonparametric regression estimator that uses prior information on regression shape in the form of a parametric model. In eeect, we nonparametrically encompass the parametric model. We obtain estimates of the regression function and its derivatives along with local parameter estimates that can be interpreted from within the parametric model. We establish the uniform consistenc...

We introduce a new nonparametric regression estimator that uses prior information on regression shape in the form of a parametric model. In e!ect, we nonparametrically encompass the parametric model. We obtain estimates of the regression function and its derivatives along with local parameter estimates that can be interpreted from within the parametric model. We establish the uniform consistenc...

In this article, we propose generalized two-parameter (GTP) estimators and an algorithm for the estimation of shrinkage parameters to combat multicollinearity in multinomial logit regression model. addition, mean squared error properties are derived. A simulation study is conducted investigate performance proposed different sample sizes, degrees multicollinearity, number explanatory variables. ...

We propose a nonparametric approach for estimating single-index, binarychoice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without specifying a parametric probability function a priori; second, we estimate the unknown probability function using kerne...

the present study aim is to offer a systematic method of assessing the credit risk of banks and also to identify key indicators using decision making trial and evaluation laboratory (dematel) technique as well as using logit regression in order to predict the credit risk of listed banks. the population of the study consists of the legal clients of the bank (ansar bank, bank saderat iran, bank m...