bayesm: Bayesian Inference for Marketing/Micro-Econometrics

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

AuthorPeter Rossi <perossichi@gmail.com>
Date of publication2015-06-20 08:33:45
MaintainerPeter Rossi <perossichi@gmail.com>
LicenseGPL (>= 2)
Version3.0-2
http://www.perossi.org/home/bsm-1

View on CRAN

Man pages

bank: Bank Card Conjoint Data of Allenby and Ginter (1995)

breg: Posterior Draws from a Univariate Regression with Unit Error...

cgetC: Obtain A List of Cut-offs for Scale Usage Problems

cheese: Sliced Cheese Data

clusterMix: Cluster Observations Based on Indicator MCMC Draws

condMom: Computes Conditional Mean/Var of One Element of MVN given All...

createX: Create X Matrix for Use in Multinomial Logit and Probit...

customerSat: Customer Satisfaction Data

detailing: Physician Detailing Data from Manchanda et al (2004)

eMixMargDen: Compute Marginal Densities of A Normal Mixture Averaged over...

fsh: Flush Console Buffer

ghkvec: Compute GHK approximation to Multivariate Normal Integrals

llmnl: Evaluate Log Likelihood for Multinomial Logit Model

llmnp: Evaluate Log Likelihood for Multinomial Probit Model

llnhlogit: Evaluate Log Likelihood for non-homothetic Logit Model

lndIChisq: Compute Log of Inverted Chi-Squared Density

lndIWishart: Compute Log of Inverted Wishart Density

lndMvn: Compute Log of Multivariate Normal Density

lndMvst: Compute Log of Multivariate Student-t Density

logMargDenNR: Compute Log Marginal Density Using Newton-Raftery Approx

margarine: Household Panel Data on Margarine Purchases

mixDen: Compute Marginal Density for Multivariate Normal Mixture

mixDenBi: Compute Bivariate Marginal Density for a Normal Mixture

mnlHess: Computes -Expected Hessian for Multinomial Logit

mnpProb: Compute MNP Probabilities

momMix: Compute Posterior Expectation of Normal Mixture Model Moments

nmat: Convert Covariance Matrix to a Correlation Matrix

numEff: Compute Numerical Standard Error and Relative Numerical...

orangeJuice: Store-level Panel Data on Orange Juice Sales

plot.bayesm.hcoef: Plot Method for Hierarchical Model Coefs

plot.bayesm.mat: Plot Method for Arrays of MCMC Draws

plot.bayesm.nmix: Plot Method for MCMC Draws of Normal Mixtures

rbayesBLP: Bayesian Analysis of Random Coefficient Logit Models Using...

rbiNormGibbs: Illustrate Bivariate Normal Gibbs Sampler

rbprobitGibbs: Gibbs Sampler (Albert and Chib) for Binary Probit

rdirichlet: Draw From Dirichlet Distribution

rDPGibbs: Density Estimation with Dirichlet Process Prior and Normal...

rhierBinLogit: MCMC Algorithm for Hierarchical Binary Logit

rhierLinearMixture: Gibbs Sampler for Hierarchical Linear Model

rhierLinearModel: Gibbs Sampler for Hierarchical Linear Model

rhierMnlDP: MCMC Algorithm for Hierarchical Multinomial Logit with...

rhierMnlRwMixture: MCMC Algorithm for Hierarchical Multinomial Logit with...

rhierNegbinRw: MCMC Algorithm for Negative Binomial Regression

rivDP: Linear "IV" Model with DP Process Prior for Errors

rivGibbs: Gibbs Sampler for Linear "IV" Model

rmixGibbs: Gibbs Sampler for Normal Mixtures w/o Error Checking

rmixture: Draw from Mixture of Normals

rmnlIndepMetrop: MCMC Algorithm for Multinomial Logit Model

rmnpGibbs: Gibbs Sampler for Multinomial Probit

rmultireg: Draw from the Posterior of a Multivariate Regression

rmvpGibbs: Gibbs Sampler for Multivariate Probit

rmvst: Draw from Multivariate Student-t

rnegbinRw: MCMC Algorithm for Negative Binomial Regression

rnmixGibbs: Gibbs Sampler for Normal Mixtures

rordprobitGibbs: Gibbs Sampler for Ordered Probit

rscaleUsage: MCMC Algorithm for Multivariate Ordinal Data with Scale Usage...

rsurGibbs: Gibbs Sampler for Seemingly Unrelated Regressions (SUR)

rtrun: Draw from Truncated Univariate Normal

runireg: IID Sampler for Univariate Regression

runiregGibbs: Gibbs Sampler for Univariate Regression

rwishart: Draw from Wishart and Inverted Wishart Distribution

Scotch: Survey Data on Brands of Scotch Consumed

simnhlogit: Simulate from Non-homothetic Logit Model

summary.bayesm.mat: Summarize Mcmc Parameter Draws

summary.bayesm.nmix: Summarize Draws of Normal Mixture Components

summary.bayesm.var: Summarize Draws of Var-Cov Matrices

tuna: Data on Canned Tuna Sales

Files in this package

bayesm
bayesm/inst
bayesm/inst/include
bayesm/inst/include/bayesm.h
bayesm/src
bayesm/src/rmixGibbs_rcpp.cpp
bayesm/src/rDPGibbs_rcpp_loop.cpp
bayesm/src/Makevars
bayesm/src/rmvst_rcpp.cpp
bayesm/src/rmnpGibbs_rcpp_loop.cpp
bayesm/src/runireg_rcpp_loop.cpp
bayesm/src/rhierLinearMixture_rcpp_loop.cpp
bayesm/src/lndMvn_rcpp.cpp
bayesm/src/llmnl_rcpp.cpp
bayesm/src/functionTiming.cpp
bayesm/src/rivDP_rcpp_loop.cpp
bayesm/src/rwishart_rcpp.cpp
bayesm/src/lndIChisq_rcpp.cpp
bayesm/src/rnmixGibbs_rcpp_loop.cpp
bayesm/src/lndMvst_rcpp.cpp
bayesm/src/rdirichlet_rcpp.cpp
bayesm/src/rhierLinearModel_rcpp_loop.cpp
bayesm/src/utilityFunctions.cpp
bayesm/src/rordprobitGibbs_rcpp_loop.cpp
bayesm/src/rhierMnlRwMixture_rcpp_loop.cpp
bayesm/src/bayesBLP_rcpp_loop.cpp
bayesm/src/ghkvec_rcpp.cpp
bayesm/src/rivgibbs_rcpp_loop.cpp
bayesm/src/rmultireg_rcpp.cpp
bayesm/src/rcppexports.cpp
bayesm/src/rsurGibbs_rcpp_loop.cpp
bayesm/src/rnegbinRw_rcpp_loop.cpp
bayesm/src/rscaleUsage_rcpp_loop.cpp
bayesm/src/runiregGibbs_rcpp_loop.cpp
bayesm/src/clusterMix_rcpp_loop.cpp
bayesm/src/rtrun_rcpp.cpp
bayesm/src/Makevars.win
bayesm/src/rhierNegbinRw_rcpp_loop.cpp
bayesm/src/rmixture_rcpp.cpp
bayesm/src/rmvpGibbs_rcpp_loop.cpp
bayesm/src/cgetC_rcpp.cpp
bayesm/src/rmnlIndepMetrop_rcpp_loop.cpp
bayesm/src/lndIWishart_rcpp.cpp
bayesm/src/breg_rcpp.cpp
bayesm/src/rbprobitGibbs_rcpp_loop.cpp
bayesm/src/rhierMnlDP_rcpp_loop.cpp
bayesm/NAMESPACE
bayesm/data
bayesm/data/detailing.rda
bayesm/data/bank.rda
bayesm/data/orangeJuice.rda
bayesm/data/tuna.rda
bayesm/data/margarine.rda
bayesm/data/Scotch.rda
bayesm/data/cheese.rda
bayesm/data/customerSat.rda
bayesm/R
bayesm/R/runireggibbs_rcpp.r
bayesm/R/nmat.R bayesm/R/condMom.R
bayesm/R/runireg_rcpp.r
bayesm/R/momMix.R
bayesm/R/rnegbinrw_rcpp.r
bayesm/R/simnhlogit.R bayesm/R/llmnp.R
bayesm/R/rordprobitgibbs_rcpp.r
bayesm/R/rhiernegbinrw_rcpp.r
bayesm/R/mixDenBi.R bayesm/R/createX.R bayesm/R/plot.bayesm.nmix.R bayesm/R/logMargDenNR.R bayesm/R/mnpProb.R bayesm/R/BayesmFunctions.R
bayesm/R/rdpgibbs_rcpp.r
bayesm/R/rmnlIndepMetrop_rcpp.R bayesm/R/rbayesBLP_rcpp.R bayesm/R/numEff.R bayesm/R/eMixMargDen.R bayesm/R/mixDen.R bayesm/R/fsh.R
bayesm/R/rbprobitgibbs_rcpp.r
bayesm/R/summary.bayesm.mat.R
bayesm/R/rsurgibbs_rcpp.r
bayesm/R/rivGibbs_rcpp.R
bayesm/R/rmnpgibbs_rcpp.r
bayesm/R/BayesmConstants.R
bayesm/R/rcppexports.r
bayesm/R/plot.bayesm.hcoef.R bayesm/R/plot.bayesm.mat.R bayesm/R/rhierLinearModel_rcpp.R
bayesm/R/rnmixgibbs_rcpp.r
bayesm/R/rbiNormGibbs.R bayesm/R/summary.bayesm.var.R
bayesm/R/rhierLinearMixture_rcpp.r
bayesm/R/llnhlogit.R
bayesm/R/rmvpgibbs_rcpp.r
bayesm/R/rhierBinLogit.R
bayesm/R/rscaleusage_rcpp.r
bayesm/R/summary.bayesm.nmix.R
bayesm/R/rhierMnlDP_rcpp.r
bayesm/R/rhierMnlRwMixture_rcpp.r
bayesm/R/clusterMix_rcpp.R bayesm/R/mnlHess.R bayesm/R/rivDP_rcpp.R
bayesm/MD5
bayesm/DESCRIPTION
bayesm/man
bayesm/man/simnhlogit.Rd bayesm/man/rmnlIndepMetrop.Rd bayesm/man/summary.bayesm.mat.Rd bayesm/man/ghkvec.Rd bayesm/man/clusterMix.Rd bayesm/man/mixDenBi.Rd bayesm/man/rbayesBLP.Rd bayesm/man/rnegbinRw.Rd bayesm/man/rhierNegbinRw.Rd bayesm/man/rhierLinearModel.Rd bayesm/man/llnhlogit.Rd bayesm/man/rbprobitGibbs.Rd bayesm/man/rmvst.Rd bayesm/man/rmultireg.Rd bayesm/man/runireg.Rd bayesm/man/cgetC.Rd bayesm/man/lndMvn.Rd bayesm/man/mixDen.Rd bayesm/man/lndIWishart.Rd bayesm/man/lndMvst.Rd bayesm/man/lndIChisq.Rd bayesm/man/rmnpGibbs.Rd bayesm/man/nmat.Rd bayesm/man/orangeJuice.Rd bayesm/man/rdirichlet.Rd bayesm/man/momMix.Rd bayesm/man/mnpProb.Rd bayesm/man/tuna.Rd bayesm/man/mnlHess.Rd bayesm/man/Scotch.Rd bayesm/man/rnmixGibbs.Rd bayesm/man/rtrun.Rd bayesm/man/rmixGibbs.Rd bayesm/man/rbiNormGibbs.Rd bayesm/man/rhierMnlDP.Rd bayesm/man/rhierBinLogit.Rd bayesm/man/rscaleUsage.Rd bayesm/man/eMixMargDen.Rd bayesm/man/rivGibbs.Rd bayesm/man/plot.bayesm.hcoef.Rd bayesm/man/breg.Rd bayesm/man/rhierLinearMixture.Rd bayesm/man/condMom.Rd bayesm/man/llmnp.Rd bayesm/man/rmvpGibbs.Rd bayesm/man/logMargDenNR.Rd bayesm/man/rhierMnlRwMixture.Rd bayesm/man/customerSat.Rd bayesm/man/margarine.Rd bayesm/man/summary.bayesm.var.Rd bayesm/man/summary.bayesm.nmix.Rd bayesm/man/plot.bayesm.mat.Rd bayesm/man/rsurGibbs.Rd bayesm/man/llmnl.Rd bayesm/man/bank.Rd bayesm/man/rmixture.Rd bayesm/man/rDPGibbs.Rd bayesm/man/createX.Rd bayesm/man/plot.bayesm.nmix.Rd bayesm/man/rordprobitGibbs.Rd bayesm/man/fsh.Rd bayesm/man/numEff.Rd bayesm/man/cheese.Rd bayesm/man/detailing.Rd bayesm/man/runiregGibbs.Rd bayesm/man/rwishart.Rd bayesm/man/rivDP.Rd

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