Provides functions for estimating Bayesian quantile regression for ordinal models, calculating covariate effects, and computing measures for model comparison. Specifically, the package offers two estimation functions - one for an ordinal model with more than three outcomes. For each ordinal model, the package provides functions to calculate the covariate effect using the MCMC outputs. The package also computes marginal likelihood (recommended) and the Deviance Information Criterion (DIC) for comparing alternative quantile regression models. Besides, the package also contains functions for making trace plots of MCMC draws and other functions that aids the estimation or inference of quantile ordinal models.
License: GPL (>=2)
Package bqror provides the following functions:
For an Ordinal Model with three outcomes:
For an Ordinal Model with more than three outcomes:
Mohammad Arshad Rahman
Prajual Maheshwari <email@example.com>
Rahman, M. A. (2016). “Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24. DOI: 10.1214/15-BA939
Yu, K., and Moyeed, R. A. (2001). “Bayesian Quantile Regression.” Statistics and Probability Letters, 54(4): 437–447. DOI: 10.1016/S0167-7152(01)00124-9
Koenker, R., and Bassett, G. (1978).“Regression Quantiles.” Econometrica, 46(1): 33-50. DOI: 10.2307/1913643
Greenberg, E. (2012). “Introduction to Bayesian Econometrics.” Cambridge University Press. Cambridge, DOI: 10.1017/CBO9781139058414
rgig, mvrnorm, ginv, rtruncnorm, mvnpdf, rinvgamma, mldivide, rand, qnorm, rexp, rnorm, std, sd, acf, Reshape, setTkProgressBar, tkProgressBar, dinvgamma
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