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
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