Bayesian Quantile Regression for Ordinal Models
MASS, pracma, tcltk, GIGrvg, truncnorm, NPflow, invgamma
c(person("Dr. Mohammad Arshad Rahman", "Developer", role = "aut",
email = c("arshadrahman25@gmail.com","marshad@iitk.ac.in")),
person("Prajual Maheshwari", role = "cre", email = "prajual1391@gmail.com"))
Provides an estimation technique for Bayesian quantile
regression in ordinal models. Two algorithms are considered - one
for an ordinal model with three outcomes and the other for an ordinal
model with more than 3 outcomes. It further provides model performance
criteria and trace plots for Markov chain Monte Carlo (MCMC) draws.
Rahman, M. A. (2016) <doi:10.1214/15-BA939>.
Greenberg, E. (2012) <doi:10.1017/CBO9781139058414>.
Spiegelhalter, D. J., Best, N. G., Carlin B. P. and Linde A. (2002) <doi:10.1111/1467-9868.00353>.
Dr. Mohammad Arshad Rahman Developer [aut],
Prajual Maheshwari [cre]

MASS, pracma, tcltk, GIGrvg, truncnorm, NPflow, invgamma,
graphics, stats
c(person("Prof. Mohammad Arshad Rahman", "Developer", role = "aut",
email = c("arshadrahman25@gmail.com","marshad@iitk.ac.in")),
person("Prajual Maheshwari", role = "cre", email = "prajual1391@gmail.com"))
Prof. Mohammad Arshad Rahman Developer [aut],
Prajual Maheshwari [cre]

c(person("Mohammad Arshad Rahman", "Developer", role = "aut",
email = c("arshadrahman25@gmail.com","marshad@iitk.ac.in")),
person("Prajual Maheshwari", role = "cre", email = "prajual1391@gmail.com"))
Provides functions for estimating Bayesian quantile regression
for ordinal models, calculating covariate effects, and computing measures for
model comparision. 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.
Rahman, M. A. (2016).“Bayesian Quantile Regression for Ordinal Models.” Bayesian
Analysis, II(I): 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>.
Chib, S. (1995). “Marginal likelihood from the Gibbs output.” Journal of
the American Statistical Association, 90(432):1313–1321, 1995. <doi: 10.1080/01621459.1995.10476635>.
Chib, S., and Jeliazkov, I. (2001). “Marginal likelihood from the
Metropolis-Hastings output.” Journal of the American Statistical Association, 96(453):270–281, 2001. <doi: 10.1198/016214501750332848>.
Mohammad Arshad Rahman Developer [aut],
Prajual Maheshwari [cre]