| Name : R-bqror
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| Version : 1.7.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp155.5.1
| Date : 2024-09-23 15:50:57
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| Group : Development/Libraries/Other
| Source RPM : R-bqror-1.7.0-lp155.5.1.src.rpm
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| Size : 0.29 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Bayesian Quantile Regression for Ordinal Models
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Description :
Package provides functions for estimation and inference in Bayesian
quantile regression with ordinal outcomes. An ordinal model with 3 or
more outcomes (labeled OR1 model) is estimated by a combination of
Gibbs sampling and Metropolis-Hastings (MH) algorithm. Whereas an
ordinal model with exactly 3 outcomes (labeled OR2 model) is estimated
using a Gibbs sampling algorithm. The summary output presents the
posterior mean, posterior standard deviation, 95% credible intervals,
and the inefficiency factors along with the two model comparison
measures – logarithm of marginal likelihood and the deviance
information criterion (DIC). The package also provides functions for
computing the covariate effects and other functions that aids either
the estimation or inference in quantile ordinal models. 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>. 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>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.5/x86_64 |
