Package: bayesm 3.1-6

Peter Rossi

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 first edition 2005 and second forthcoming) and Bayesian Non- and Semi-Parametric Methods and Applications (Princeton U Press 2014).

Authors:Peter Rossi <[email protected]>

bayesm_3.1-6.tar.gz
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bayesm.pdf |bayesm.html✨
bayesm/json (API)

# Install 'bayesm' in R:
install.packages('bayesm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • Scotch - Survey Data on Brands of Scotch Consumed
  • bank - Bank Card Conjoint Data
  • camera - Conjoint Survey Data for Digital Cameras
  • cheese - Sliced Cheese Data
  • customerSat - Customer Satisfaction Data
  • detailing - Physician Detailing Data
  • margarine - Household Panel Data on Margarine Purchases
  • orangeJuice - Store-level Panel Data on Orange Juice Sales
  • tuna - Canned Tuna Sales Data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

58 exports 19 stars 4.48 score 2 dependencies 36 dependents 1 mentions 294 scripts 6.2k downloads

Last updated 12 months agofrom:aa87c96e5c. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 19 2024
R-4.5-linux-x86_64NOTEAug 19 2024

Exports:bregcgetCclusterMixcondMomcreateXeMixMargDenghkvecllmnlllmnpllnhlogitlndIChisqlndIWishartlndMvnlndMvstlogMargDenNRmixDenmixDenBimnlHessmnpProbmomMixnmatnumEffplot.bayesm.hcoefplot.bayesm.matplot.bayesm.nmixrbayesBLPrbiNormGibbsrbprobitGibbsrdirichletrDPGibbsrhierBinLogitrhierLinearMixturerhierLinearModelrhierMnlDPrhierMnlRwMixturerhierNegbinRwrivDPrivGibbsrmixGibbsrmixturermnlIndepMetroprmnpGibbsrmultiregrmvpGibbsrmvstrnegbinRwrnmixGibbsrordprobitGibbsrscaleUsagersurGibbsrtrunruniregruniregGibbsrwishartsimnhlogitsummary.bayesm.matsummary.bayesm.nmixsummary.bayesm.var

Dependencies:RcppRcppArmadillo

bayesm Overview

Rendered frombayesm_Overview_Vignette.Rmdusingknitr::rmarkdownon Aug 19 2024.

Last update: 2022-12-02
Started: 2017-06-25

Hierarchical Multinomial Logit with Sign Constraints

Rendered fromConstrained_MNL_Vignette.Rmdusingknitr::rmarkdownon Aug 19 2024.

Last update: 2019-07-13
Started: 2017-06-25

Readme and manuals

Help Manual

Help pageTopics
Bank Card Conjoint Databank
Posterior Draws from a Univariate Regression with Unit Error Variancebreg
Conjoint Survey Data for Digital Camerascamera
Obtain A List of Cut-offs for Scale Usage ProblemscgetC
Sliced Cheese Datacheese
Cluster Observations Based on Indicator MCMC DrawsclusterMix
Computes Conditional Mean/Var of One Element of MVN given All OtherscondMom
Create X Matrix for Use in Multinomial Logit and Probit RoutinescreateX
Customer Satisfaction DatacustomerSat
Physician Detailing Datadetailing
Compute Marginal Densities of A Normal Mixture Averaged over MCMC DrawseMixMargDen
Compute GHK approximation to Multivariate Normal Integralsghkvec
Evaluate Log Likelihood for Multinomial Logit Modelllmnl
Evaluate Log Likelihood for Multinomial Probit Modelllmnp
Evaluate Log Likelihood for non-homothetic Logit Modelllnhlogit
Compute Log of Inverted Chi-Squared DensitylndIChisq
Compute Log of Inverted Wishart DensitylndIWishart
Compute Log of Multivariate Normal DensitylndMvn
Compute Log of Multivariate Student-t DensitylndMvst
Compute Log Marginal Density Using Newton-Raftery ApproxlogMargDenNR
Household Panel Data on Margarine Purchasesmargarine
Compute Marginal Density for Multivariate Normal MixturemixDen
Compute Bivariate Marginal Density for a Normal MixturemixDenBi
Computes -Expected Hessian for Multinomial LogitmnlHess
Compute MNP ProbabilitiesmnpProb
Compute Posterior Expectation of Normal Mixture Model MomentsmomMix
Convert Covariance Matrix to a Correlation Matrixnmat
Compute Numerical Standard Error and Relative Numerical EfficiencynumEff
Store-level Panel Data on Orange Juice SalesorangeJuice
Plot Method for Hierarchical Model Coefsplot.bayesm.hcoef
Plot Method for Arrays of MCMC Drawsplot.bayesm.mat
Plot Method for MCMC Draws of Normal Mixturesplot.bayesm.nmix
Bayesian Analysis of Random Coefficient Logit Models Using Aggregate DatarbayesBLP
Illustrate Bivariate Normal Gibbs SamplerrbiNormGibbs
Gibbs Sampler (Albert and Chib) for Binary ProbitrbprobitGibbs
Draw From Dirichlet Distributionrdirichlet
Density Estimation with Dirichlet Process Prior and Normal BaserDPGibbs
MCMC Algorithm for Hierarchical Binary LogitrhierBinLogit
Gibbs Sampler for Hierarchical Linear Model with Mixture-of-Normals HeterogeneityrhierLinearMixture
Gibbs Sampler for Hierarchical Linear Model with Normal HeterogeneityrhierLinearModel
MCMC Algorithm for Hierarchical Multinomial Logit with Dirichlet Process Prior HeterogeneityrhierMnlDP
MCMC Algorithm for Hierarchical Multinomial Logit with Mixture-of-Normals HeterogeneityrhierMnlRwMixture
MCMC Algorithm for Hierarchical Negative Binomial RegressionrhierNegbinRw
Linear "IV" Model with DP Process Prior for ErrorsrivDP
Gibbs Sampler for Linear "IV" ModelrivGibbs
Gibbs Sampler for Normal Mixtures w/o Error CheckingrmixGibbs
Draw from Mixture of Normalsrmixture
MCMC Algorithm for Multinomial Logit ModelrmnlIndepMetrop
Gibbs Sampler for Multinomial ProbitrmnpGibbs
Draw from the Posterior of a Multivariate Regressionrmultireg
Gibbs Sampler for Multivariate ProbitrmvpGibbs
Draw from Multivariate Student-trmvst
MCMC Algorithm for Negative Binomial RegressionrnegbinRw
Gibbs Sampler for Normal MixturesrnmixGibbs
Gibbs Sampler for Ordered ProbitrordprobitGibbs
MCMC Algorithm for Multivariate Ordinal Data with Scale Usage HeterogeneityrscaleUsage
Gibbs Sampler for Seemingly Unrelated Regressions (SUR)rsurGibbs
Draw from Truncated Univariate Normalrtrun
IID Sampler for Univariate Regressionrunireg
Gibbs Sampler for Univariate RegressionruniregGibbs
Draw from Wishart and Inverted Wishart Distributionrwishart
Survey Data on Brands of Scotch ConsumedScotch
Simulate from Non-homothetic Logit Modelsimnhlogit
Summarize Mcmc Parameter Drawssummary.bayesm.mat
Summarize Draws of Normal Mixture Componentssummary.bayesm.nmix
Summarize Draws of Var-Cov Matricessummary.bayesm.var
Canned Tuna Sales Datatuna