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HETOP (version 0.2-6)

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

Description

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

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Version

Install

install.packages('HETOP')

Monthly Downloads

28

Version

0.2-6

License

GPL (>= 2)

Maintainer

J.R. Lockwood

Last Published

June 28th, 2019

Functions in HETOP (0.2-6)

fh_hetop

Fit Fay-Herriot Heteroskedastic Ordered Probit (FH-HETOP) Model using JAGS
mle_hetop

Maximum Likelihood Estimation of Heteroskedastic Ordered Probit (HETOP) Model
waic_hetop

WAIC for FH-HETOP model
triple_goal

Shen and Louis (1998) Triple Goal Estimators
gendata_hetop

Generate count data from Heteroskedastic Ordered Probit (HETOP) Model