Testing the Accuracy, Usefulness, and Significance of Probabilistic Choice Models: An Information-Theoretic Approach

DOI10.1287/opre.26.3.406zbMath0382.90007OpenAlexW1983004841MaRDI QIDQ4160625

Publication date: 1978

Published in: Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/opre.26.3.406

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric hypothesis testing (62G10) Decision theory (91B06) Information theory (general) (94A15) Statistical aspects of information-theoretic topics (62B10)

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Implications and relative fit of several first-order Markov models of consumer variety seeking ⋮ Statistical mechanics of choice: MaxEnt estimation of population heterogeneity ⋮ Customer-base analysis using repeated cross-sectional summary (RCSS) data ⋮ An \(R\)-squared measure of goodness of fit for some common nonlinear regression models ⋮ Information theory as a unifying statistical approach for use in marketing research ⋮ Goodness-of-fit measures in binary choice models¹ ⋮ Things that make us different: analysis of deviance with time-use data ⋮ Approximation Algorithms for Product Framing and Pricing ⋮ A stochastic multidimensional unfolding approach for representing phased decision outcomes ⋮ A framework to determine the value of consumer consideration set information for firm pricing strategies ⋮ Discrete choice models based on random walks

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