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).

Author
Peter Rossi <perossichi@gmail.com>
Date of publication
2015-06-20 08:33:45
Maintainer
Peter Rossi <perossichi@gmail.com>
License
GPL (>= 2)
Version
3.0-2
URLs

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