Mixed logit models: accuracy and software choice

2010 ◽  
Vol 26 (1) ◽  
pp. 167-172 ◽  
Author(s):  
Jae Bong Chang ◽  
Jayson L. Lusk
Keyword(s):  
Mixed Logit ◽  
Logit Models ◽  
Mixed Logit Models

Including cost income ratio into utility function as a way of dealing with ‘exploding’ implicit prices in mixed logit models

2012 ◽  
Vol 18 (4) ◽  
pp. 370-380 ◽  
Author(s):  
Marek Giergiczny ◽  
Sviataslau Valasiuk ◽  
Mikolaj Czajkowski ◽  
Maria De Salvo ◽  
Giovanni Signorello
Keyword(s):  
Utility Function ◽  
Mixed Logit ◽  
Logit Models ◽  
Mixed Logit Models ◽  
Income Ratio ◽  
Implicit Prices

scholarly journals A Trip Purpose-Based Data-Driven Alighting Station Choice Model Using Transit Smart Card Data

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Kai Lu ◽  
Alireza Khani ◽  
Baoming Han
Keyword(s):  
Open Systems ◽  
Choice Model ◽  
Mixed Logit ◽  
Random Coefficients ◽  
Logit Models ◽  
Transit Systems ◽  
Trip Purpose ◽  
Mixed Logit Models ◽  
Key Factor ◽  
Rich Data

Automatic fare collection (AFC) systems have been widely used all around the world which record rich data resources for researchers mining the passenger behavior and operation estimation. However, most transit systems are open systems for which only boarding information is recorded but the alighting information is missing. Because of the lack of trip information, validation of utility functions for passenger choices is difficult. To fill the research gaps, this study uses the AFC data from Beijing metro, which is a closed system and records both boarding information and alighting information. To estimate a more reasonable utility function for choice modeling, the study uses the trip chaining method to infer the actual destination of the trip. Based on the land use and passenger flow pattern, applying k-means clustering method, stations are classified into 7 categories. A trip purpose labelling process was proposed considering the station category, trip time, trip sequence, and alighting station frequency during five weekdays. We apply multinomial logit models as well as mixed logit models with independent and correlated normally distributed random coefficients to infer passengers’ preferences for ticket fare, walking time, and in-vehicle time towards their alighting station choice based on different trip purposes. The results find that time is a combined key factor while the ticket price based on distance is not significant. The estimated alighting stations are validated with real choices from a separate sample to illustrate the accuracy of the station choice models.

scholarly journals Fitting Mixed Logit Models by Using Maximum Simulated Likelihood

2007 ◽  
Vol 7 (3) ◽  
pp. 388-401 ◽  
Author(s):  
Arne Risa Hole
Keyword(s):  
Mixed Logit ◽  
Logit Models ◽  
Maximum Simulated Likelihood ◽  
Mixed Logit Models ◽  
Simulated Likelihood

This article describes the mixlogit Stata command for fitting mixed logit models by using maximum simulated likelihood.

scholarly journals Estimating Strawberry Attributes’ Market Equilibrium Values

HortScience ◽  
2017 ◽  
Vol 52 (5) ◽  
pp. 742-748
Author(s):  
Jong Woo Choi ◽  
Chengyan Yue ◽  
James Luby ◽  
Shuoli Zhao ◽  
Karina Gallardo ◽  
...  
Keyword(s):  
Demand Curve ◽  
Supply And Demand ◽  
Mixed Logit ◽  
Market Equilibrium ◽  
Mixed Logit Model ◽  
Logit Models ◽  
Total Revenue ◽  
Mixed Logit Models ◽  
Equilibrium Prices ◽  
Social Surplus

We conducted choice experiments with both strawberry producers and consumers. Consumer and producer willingness to pay (WTP) for the fruit attributes were estimated using mixed logit models. Through simulation using the mixed logit model results, we derived the market equilibrium prices, supply and demand curve, as well as quantities demanded and supplied for every fruit attribute. We found the highest equilibrium price was for strawberry internal color followed by flavor. Strawberry breeders can use the information when setting breeding targets, allocating resources appropriately during their breeding process and focusing on the improvement of attributes that produce the highest social surplus and total revenue.

Profile Construction in Experimental Choice Designs for Mixed Logit Models

2002 ◽  
Vol 21 (4) ◽  
pp. 455-475 ◽  
Author(s):  
Zsolt Sándor ◽  
Michel Wedel
Keyword(s):  
Mixed Logit ◽  
Logit Models ◽  
Mixed Logit Models
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