Results 1 to 10 of about 9,071 (160)

Multinomial logit death forecasting model

Lietuvos Matematikos Rinkinys, 1999
The multinomial regression logit model is analyzed. The algorithms and software are made for this model in order to get estimation of parameters. Calculations are made using generated population of 1000 cases.
Audronė Jakaitienė
doaj   +4 more sources

TÜRKİYE’DE HANEHALKLARININ BALIK TÜKETİM HARCAMALARI: LOGIT VE MULTINOMIAL LOGIT YAKLAŞIMLARI

Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2020
Çalışmada insan sağlığı üzerinde kanıtlanmış olumlu etkileri olan balık tüketiminin Türkiye hanehalkları için belirleyicileri analiz edilmiştir. Bu amaçla Türkiye İstatistik Kurumu'nun 2018 yılı Hanehalkı Bütçe Araştırması Mikro Veri Setinde yer alan 11 ...
Onur Demirel, Selim Adem Hatırlı
doaj   +4 more sources

Poverty Dynamics in Turkey: A Multinomial Logit Model

Ekonomika, 2021
The availability of longitudinal data allows researchers to analyse the dynamics of poverty. By using the Turkish Statistical Institute’s (TurkStat) Income and Living Conditions Survey micro dataset, we analyse the households’ long-term monetary poverty ...
Senem Çakmak Şahin, İbrahim Engin Kılıç   +1 more
doaj   +5 more sources

Variable selection in general multinomial logit models [PDF]

Computational Statistics and Data Analysis, 2015
The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood estimates tend to deteriorate. In this paper we are proposing a sparsity-inducing penalty that accounts for the special structure of multinomial models. In contrast to existing methods, it penalizes
Gerhard Tutz
exaly   +3 more sources

Comparing methods for risk prediction of multicategory outcomes: dichotomized logistic regression vs. multinomial logit regression [PDF]

BMC Medical Research Methodology
Background Medical outcomes of interest to clinicians may have multiple categories. Researchers face several options for risk prediction of such outcomes, including dichotomized logistic regression and multinomial logit regression modeling.
Lei Li, Matthew A. Rysavy, Georgiy Bobashev, Abhik Das   +3 more
doaj   +2 more sources

Estimating Probability of Banking Crisis using 2nd Generation Early Warning Systems: An Intercountry Study [PDF]

فصلنامه پژوهش‌های اقتصادی ایران, 2021
The main purpose of this study is to estimate the probability of banking crisis using the second generation of early warning systems (logit models), for 13 selected high-middle income countries over the period of 1980-2016.
Seyed Saleh Akbar Mousavi, Behzad Salmani, Jafar Haghighat, Hossein Asgharpour   +3 more
doaj   +1 more source

Optimal model averaging estimator for multinomial logit models

Statistical Theory and Related Fields, 2022
In this paper, we study optimal model averaging estimators of regression coefficients in a multinomial logit model, which is commonly used in many scientific fields.
Rongjie Jiang, Liming Wang, Yang Bai
doaj   +1 more source

Exploring Influencing Factors of Intercity Mode Choice from View of Entire Travel Chain

Journal of Advanced Transportation, 2021
Exploring the influencing factors of intercity travel mode choice can reveal passengers’ travel decision mechanisms and help traffic departments to develop an effective demand management policy.
Xiaowei Li, Siyu Zhang, Yao Wu, Yuting Wang, Wenbo Wang   +4 more
doaj   +1 more source

Specification Tests for the Multinomial Logit Model [PDF]

Econometrica, 1984
In the paper we provide two sets of computationally convenient specification tests for the multinomial logit model. The first test is an application of the \textit{J. Hausman} [ibid. 46, 1251-1271 (1978; Zbl 0397.62043)] specification test procedure. The basic idea for the test here is to test the reverse implication of the independence from irrelevant
Hausman, Jerry, McFadden, Daniel
openaire   +1 more source

General Deep Multinomial Logit Model

Computing and Informatics, 2022
Multinomial logit model (MNL) is by far the most widely used discrete choice model that is widely used to explain or predict a choice from a set of two or more discrete alternatives. MNL operates within a framework of the random utility model (RUM) in which the utility of an alternative perceived by an individual consists of two components: systematic ...
Su, Peng, Liu, Yuan, Zhao, Lingyun
openaire   +2 more sources