Abstract/Details

Parametric and nonparametric statistical modeling: Reliability analysis

Qiao, Hongzhu. 
 University of South Florida ProQuest Dissertations Publishing,  1993. 9323694.

Abstract (summary)

The aim of the present study is to investigate several important problems in probability distribution, reliability analysis and nonparametric probability density estimation.

Extensive investigation of the basic properties of the Weibull process/nonhomogeneous Poisson process that characterizes the reliability growth behaviors of various components and systems was performed. In addition, linearly derived best efficient estimates of the parameters of the subject process were developed. Using real world data, we have illustrated the effectiveness of the results of this study.

Computerized simple iterative procedures have been developed for estimating the two and three parameters of the Weibull probability distributions. Our procedure will always converge and converge very rapidly.

An effective method has been developed to estimate the nonparametric probability density functions of data that possesses bimodal characteristics.

Finally, a procedure has been developed to perform reliability analysis when the failure model is characterized nonparametrically.

Indexing (details)


Subject
Statistics
Classification
0463: Statistics
Identifier / keyword
Pure sciences; Weibull probability distribution; probability density estimation
Title
Parametric and nonparametric statistical modeling: Reliability analysis
Author
Qiao, Hongzhu
Number of pages
160
Degree date
1993
School code
0206
Source
DAI-B 54/04, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
979-8-207-89120-0
Advisor
Tsokos, Chris P.
University/institution
University of South Florida
University location
United States -- Florida
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
9323694
ProQuest document ID
304071001
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/304071001