HETOP: MLE and Bayesian Estimation of Heteroskedastic Ordered Probit (HETOP) Model

Provides functions for maximum likelihood and Bayesian estimation of the Heteroskedastic Ordered Probit (HETOP) model, using methods described in Lockwood, Castellano and Shear (2018) <doi:10.3102/1076998618795124> and Reardon, Shear, Castellano and Ho (2017) <doi:10.3102/1076998616666279>. It also provides a general function to compute the triple-goal estimators of Shen and Louis (1998) <doi:10.1111/1467-9868.00135>.

Version: 0.2-6
Depends: R (≥ 3.4.0), R2jags, splines, stats
Published: 2019-06-28
Author: J.R. Lockwood
Maintainer: J.R. Lockwood <jrlockwood at ets.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: HETOP results

Downloads:

Reference manual: HETOP.pdf
Package source: HETOP_0.2-6.tar.gz
Windows binaries: r-devel: HETOP_0.2-6.zip, r-release: HETOP_0.2-6.zip, r-oldrel: HETOP_0.2-6.zip
OS X binaries: r-release: HETOP_0.2-6.tgz, r-oldrel: HETOP_0.2-6.tgz

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