MONTE CARLO COMPARISON OF GOODNESS-OF-FIT TESTS FOR THE INVERSE GAUSSIAN DISTRIBUTION BASED ON EMPIRICAL DISTRIBUTION FUNCTION

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Alizadeh Noughabi Hadi; Shafaei Noughabi Mohammad

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Mahani Mathematical Research Year:2024 | Volume:13 | Issue:1 Page(s): 71-84

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

MONTE CARLO COMPARISON OF GOODNESS-OF-FIT TESTS FOR THE INVERSE GAUSSIAN DISTRIBUTION BASED ON EMPIRICAL DISTRIBUTION FUNCTION

Author(s)

Alizadeh Noughabi Hadi | Shafaei Noughabi Mohammad | Issue Writer Certificate

Keywords

:Empirical distribution function

Inverse Gaussian distribution

Maximum likelihood estimates

Goodness-of-fit test

Monte Carlo simulation

Test powe

Abstract

The Inverse Gaussian (IG) distribution is widely used to model positively skewed data. In this article, we examine goodness of fit tests for the Inverse Gaussian distribution based on the empirical distribution function. In order to compute the test statistics, parameters of the Inverse Gaussian distribution are estimated by maximum likelihood estimators (MLEs), which are simple explicit estimators. Critical points and the actual sizes of the tests are obtained by Monte Carlo simulation. Through a simulation study, power values of the tests are compared with each other. Finally, an illustrative example is presented and analyzed.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans