22 lines
1.3 KiB
Text
22 lines
1.3 KiB
Text
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Covers many important models used in marketing and micro-econometrics
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applications. The package includes: Bayes Regression (univariate or
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multivariate dep var), Bayes Seemingly Unrelated Regression (SUR),
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Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial
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Probit (MNP), Multivariate Probit, Negative Binomial (Poisson)
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Regression, Multivariate Mixtures of Normals (including clustering),
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Dirichlet Process Prior Density Estimation with normal base,
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Hierarchical Linear Models with normal prior and covariates,
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Hierarchical Linear Models with a mixture of normals prior and
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covariates, Hierarchical Multinomial Logits with a mixture of normals
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prior and covariates, Hierarchical Multinomial Logits with a Dirichlet
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Process prior and covariates, Hierarchical Negative Binomial
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Regression Models, Bayesian analysis of choice-based conjoint data,
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Bayesian treatment of linear instrumental variables models, Analysis
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of Multivariate Ordinal survey data with scale usage heterogeneity (as
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in Rossi et al, JASA (01)), Bayesian Analysis of Aggregate Random
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Coefficient Logit Models as in BLP (see Jiang, Manchanda, Rossi 2009)
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For further reference, consult our book, Bayesian Statistics and
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Marketing by Rossi, Allenby and McCulloch (Wiley 2005) and Bayesian
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Non- and Semi-Parametric Methods and Applications (Princeton U Press
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2014).
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