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HETOP  

MLE and Bayesian Estimation of Heteroskedastic Ordered Probit (HETOP) Model
View on CRAN: Click here


Download and install HETOP package within the R console
Install from CRAN:
install.packages("HETOP")

Install from Github:
library("remotes")
install_github("cran/HETOP")

Install by package version:
library("remotes")
install_version("HETOP", "0.2-6")



Attach the package and use:
library("HETOP")
Maintained by
J.R. Lockwood
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-28
Latest Update: 2019-06-28
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) .
How to cite:
J.R. Lockwood (2019). HETOP: MLE and Bayesian Estimation of Heteroskedastic Ordered Probit (HETOP) Model. R package version 0.2-6, https://cran.r-project.org/web/packages/HETOP
Previous versions and publish date:
No previous versions
Other packages that cited HETOP R package
View HETOP citation profile
Other R packages that HETOP depends, imports, suggests or enhances
Functions, R codes and Examples using the HETOP R package
Some associated functions: fh_hetop . gendata_hetop . mle_hetop . triple_goal . waic_hetop . 
Some associated R codes: fh_hetop.R . gendata_hetop.R . mle_hetop.R . triple_goal.R . waic_hetop.R .  Full HETOP package functions and examples
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