Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model

Joint Authors

Msallam, Basim Shlaibah
Kamar, Saifaldin Hashim

Source

Journal of Probability and Statistics

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-01-14

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Mathematics

Abstract EN

The Weibull growth model is an important model especially for describing the growth instability; therefore, in this paper, three methods, namely, generalized maximum entropy, Bayes, and maximum a posteriori, for estimating the four parameter Weibull growth model have been presented and compared.

To achieve this aim, it is necessary to use a simulation technique to generate the samples and perform the required comparisons, using varying sample sizes (10, 12, 15, 20, 25, and 30) and models depending on the standard deviation (0.5).

It has been shown from the computational results that the Bayes method gives the best estimates.

American Psychological Association (APA)

Kamar, Saifaldin Hashim& Msallam, Basim Shlaibah. 2020. Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model. Journal of Probability and Statistics،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1190187

Modern Language Association (MLA)

Kamar, Saifaldin Hashim& Msallam, Basim Shlaibah. Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model. Journal of Probability and Statistics No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1190187

American Medical Association (AMA)

Kamar, Saifaldin Hashim& Msallam, Basim Shlaibah. Comparative Study between Generalized Maximum Entropy and Bayes Methods to Estimate the Four Parameter Weibull Growth Model. Journal of Probability and Statistics. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1190187

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1190187