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*COLOR(red){bayesm}パッケージ(マーケティング/マイクロ計量経済学のベイズ推定)中のオブジェクト一覧 [#l7759dd5] Package: bayesm Version: 2.1-3 Date: 2007-03-28 Title: Bayesian Inference for Marketing/Micro-econometrics （マーケティング，ミクロ経済学のためのベイズ推定） |項目|説明| |Scotch| Survey Data on Brands of Scotch Consumed| |bank| Bank Card Conjoint Data of Allenby and Ginter (1995)| |breg| Posterior Draws from a Univariate Regression with Unit Error Variance| |cgetC| Obtain A List of Cut-offs for Scale Usage Problems| |cheese| スライスチーズのデータ| |clusterMix| Cluster Observations Based on Indicator MCMC Draws| |condMom| Computes Conditional Mean/Var of One Element of MVN given All Others| |createX| 多項ロジットおよびプロビットルーチンで使用する X マトリックスの計算| |customerSat| 顧客満足度データ| |detailing| Physician Detailing Data from Manchanda et al (2004)| |eMixMargDen| Compute Marginal Densities of A Normal Mixture Averaged over MCMC Draws| |fsh| Flush Console Buffer| |ghkvec| Compute GHK approximation to Multivariate Normal Integrals| |llmnl| 多項ロジットモデルの対数尤度の評価| |llmnp| 多項プロビットモデルの対数尤度の評価| |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 Efficiency| |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| |rbiNormGibbs| Illustrate Bivariate Normal Gibbs Sampler| |rbprobitGibbs| Gibbs Sampler (Albert and Chib) for Binary Probit| |rdirichlet| Draw From Dirichlet Distribution| |rhierBinLogit| MCMC Algorithm for Hierarchical Binary Logit| |rhierLinearMixture| Gibbs Sampler for Hierarchical Linear Model| |rhierLinearModel| Gibbs Sampler for Hierarchical Linear Model| |rhierMnlRwMixture| MCMC Algorithm for Hierarchical Multinomial Logit with Mixture of Normals Heterogeneity| |rhierNegbinRw| 負の二項回帰の MCMC アルゴリズム| |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 Heterogeneity| |rsurGibbs| Gibbs Sampler for Seemingly Unrelated Regressions (SUR)| |rtrun| Draw from Truncated Univariate Normal| |runireg| IID Sampler for Univariate Regression| |runiregGibbs| 単変量回帰の Gibbs サンプラ| |rwishart| Draw from Wishart and Inverted Wishart Distribution| |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| ツナ缶の売り上げデータ|
