<--- Back to Details
First PageDocument Content
Computational statistics / Regression analysis / Statistical models / Logistic regression / Artificial neural network / Logistic function / Discrete choice / Linear discriminant analysis / Consumer behaviour / Statistics / Computational neuroscience / Neural networks
Date: 2013-01-15 18:03:04
Computational statistics
Regression analysis
Statistical models
Logistic regression
Artificial neural network
Logistic function
Discrete choice
Linear discriminant analysis
Consumer behaviour
Statistics
Computational neuroscience
Neural networks

Consumer Choice Prediction: Artificial Neural Networks versus Logistic Model

Add to Reading List

Source URL: www.mssanz.org.au

Download Document from Source Website

File Size: 298,76 KB

Share Document on Facebook

Similar Documents

Semiparametric estimation of multinomial discrete-choice models using a subset of choices

DocID: 1v4Nf - View Document

Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design Igor Labutov Frans Schalekamp

DocID: 1t4G6 - View Document

Towards using Discrete Choice Experiment in modelling building retrofit Jill MADELENAT1 Abstract Buildings are the largest energy consumer both at the international and at the French levels.

DocID: 1rIMn - View Document

Economy / Economics / Business / Choice modelling / Pricing / Single-equation methods / Statistical models / Scientific modeling / Discrete choice / Service / Delivery / Post-office box

  swiss economics    

DocID: 1rjOn - View Document

Statistics / Regression analysis / Categorical data / Actuarial science / Logit / Statistical models / NLOGIT / Logistic regression / Discrete choice

On the Equivalence of Location Choice Models: Conditional Logit, Nested Logit and Poisson∗ Kurt Schmidheiny‡ Marius Br¨

DocID: 1r4gy - View Document