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OptSig  

Optimal Level of Significance for Regression and Other Statistical Tests
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("OptSig", "2.2")



Attach the package and use:
library("OptSig")
Maintained by
Jae H. Kim
[Scholar Profile | Author Map]
First Published: 2017-12-21
Latest Update: 2022-07-03
Description:
The optimal level of significance is calculated based on a decision-theoretic approach. The optimal level is chosen so that the expected loss from hypothesis testing is minimized. A range of statistical tests are covered, including the test for the population mean, population proportion, and a linear restriction in a multiple regression model. The details are covered in Kim and Choi (2020) , and Kim (2021) .
How to cite:
Jae H. Kim (2017). OptSig: Optimal Level of Significance for Regression and Other Statistical Tests. R package version 2.2, https://cran.r-project.org/web/packages/OptSig. Accessed 03 Jun. 2025.
Previous versions and publish date:
1.0 (2017-12-21 11:26), 2.0 (2019-09-08 12:30), 2.1 (2020-04-18 09:40)
Other packages that cited OptSig R package
View OptSig citation profile
Other R packages that OptSig depends, imports, suggests or enhances
Complete documentation for OptSig
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