scholarly journals Shrinkage Estimation in the Random Parameters Logit Model

2016 ◽  
Vol 06 (04) ◽  
pp. 667-674 ◽  
Author(s):  
Tong Zeng ◽  
R. Carter Hill
Keyword(s):  
Logit Model ◽  
Shrinkage Estimation ◽  
Random Parameters ◽  
Random Parameters Logit

scholarly journals Heterogeneidad de preferencias y experimentos de elección: Aplicación de un logit con parámetros aleatorios a la demanda de nueces

2011 ◽  
Vol 4 (8) ◽  
pp. 105
Author(s):  
Dena M. Camarena ◽  
Ana I. Sanjuán
Keyword(s):  
Logit Model ◽  
Choice Experiment ◽  
Mixed Logit ◽  
Stated Preferences ◽  
Attribute Level ◽  
Random Parameters ◽  
Random Parameters Logit ◽  
Independence Of Irrelevant Alternatives

Consumers’ stated preferences towards walnuts are studied by means of a choice experiment, with a double objective: first, to identify the main attributes searched by consumer at purchase and second, to analyse the chances for the introduction into the Spanish market of the Pecan variety. From this study, commercial guidelines may be derived, that helps distribution and import companies to commercialise this nut. A mixed or random parameters logit is estimated which relaxes the IIA property (independence of irrelevant alternatives) present in the logit model with fixed parameters. In a mixed logit, coefficients of each attribute/level vary randomly across consumers, reflecting the heterogeneity of individuals’ preferences. This model also allows estimate efficiently the parameters when each individual chooses several times, as in the present study.

scholarly journals Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

2021 ◽  
Vol 11 (17) ◽  
pp. 7819
Author(s):  
Fulu Wei ◽  
Zhenggan Cai ◽  
Zhenyu Wang ◽  
Yongqing Guo ◽  
Xin Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spatial Correlation ◽  
Traffic Safety ◽  
Logit Model ◽  
Unobserved Heterogeneity ◽  
Crash Severity ◽  
Random Parameters ◽  
Crash Data ◽  
Random Parameters Logit ◽  
Single Vehicle

The effect of risk factors on crash severity varies across vehicle types. The objective of this study was to explore the risk factors associated with the severity of rural single-vehicle (SV) crashes. Four vehicle types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity and spatial correlation in crash data, a novel Bayesian spatial random parameters logit (SRP-logit) model is proposed. Rural SV crash data in Shandong Province were extracted to calibrate the model. Three traditional logit approaches—multinomial logit model, random parameter logit model, and random intercept logit model—were also established and compared with the proposed model. The results indicated that the SRP-logit model exhibits the best fit performance compared with other models, highlighting that simultaneously accommodating unobserved heterogeneity and spatial correlation is a promising modeling approach. Further, there is a significant positive correlation between weekend, dark (without street lighting) conditions, and collision with fixed object and severe crashes and a significant negative correlation between collision with pedestrians and severe crashes. The findings can provide valuable information for policy makers to improve traffic safety performance in rural areas.

scholarly journals MODELLING PERCEIVED QUALITY FOR URBAN TRANSPORT SYSTEMS USING WEIGHTED VARIABLES AND RANDOM PARAMETERS

2016 ◽  
Author(s):  
Eneko Echaniz Beneitez ◽  
Luigi Dell'Olio ◽  
Angel Ibeas Portilla
Keyword(s):  
Logit Model ◽  
Urban Transport ◽  
Model Fit ◽  
The Other ◽  
Transport Systems ◽  
Generic Model ◽  
Random Parameters ◽  
Ordered Logit Model ◽  
New Models ◽  
Complexity Increase

In this article, an Ordered Logit model is proposed considering systematic and random variations in tastes. The methodology followed for the creation of this model consisted, in first place, in obtaining data using a revelled preferences survey. In the survey, each user had to evaluate, following a qualitative scale, each one of the attributes of the analysed transport system. The variables evaluated in the survey had been grouped into six groups, and for each group, users had to order the attributes belonging to the group, using a ranking based method, from the most important to de least important, and, in the same way, with the groups itself. Once the database is formed, a generic model have been created, establishing this model as a comparative base for the rest. Next, two more models have been estimated one considering systematic users variations and the other one combining the systematic variations with weighted variables. Additionally, three new models have been calculated as an evolution of the previous ones using random variables as representation of systematic and random variations in user’s tastes. The results shows that as model’s complexity increase, an improvement in model fit is achieved.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4072

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