We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditional probability tables (CPT), logit models, decision trees or hybrid models, i.e., combinations of the three. We compare this method with alternative local structure learning algorithms using the MDL and BDe metrics. Results a...

Richard Baskerville and Nancy Russo have shown how particular supervisor-student relationships can be seen as one of a number of metaphors, for example, a journey, a marriage, apprenticeship and servitude. In this paper we develop this idea further by suggesting problems associated with situations where students and supervisors might be proceeding on the basis of different metaphors, which we r...

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The simulation variance in the estimation of mixed logit parameters is found, in our application, to be lower with 100 Halton draws than with 1000 random draws. This finding confirms Bhat’s (1999a) results and implies significant reduction in run times for mixed logit estimation. Further investigation is needed to assure that the result is not quixotic or masking other issues.

In this article we analyze several optimization methods of a real-life nonlinear optimization problem in R. The optimization problem results from fitting a multinomial logit-model. This is part of the so called Brand Simulator, a tool to forecast and simulate possible marketing mixes. In the existing optimization procedure, simple derivation-free techniques are used. The objective of this paper...

This paper compares the leading models of strategic thinking with subjects’ initial responses to Van Huyck et al.’s (1990, 1991; “VHBB”) coordination games. The data favor models in which players treat their partners’ decisions as correlated rather than independent. Among the equilibrium selection criteria we compare, payoff-dominant equilibrium fits better than risk-dominant equilibrium or a s...

We derive a simple result that allows us to test for the presence of state dependence in a dynamic Logit model with time-variant transition probabilities and an arbitrary distribution of the unobserved heterogeneity. Monte Carlo evidence suggests that this test has desirable properties even when there are some violations of the model’s assumptions. We also consider alternative tests that will h...

The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated preference data. It is timely to review progress in model estimation since the learning curve is steep and the unw...

 Joint Optimization of Assortment Selection and Pricing under the Capacitated Multinomial Logit Choice Model with Product-Differentiated Price Sensitivities Ruxian Wang HP Laboratories HPL-2012-207 Multinomial Logit model; assortment optimization; multi-product price optimization Many firms face a problem to select an assortment of products and determine their prices to maximize the total prof...