Novel nonlinear least square parameter estimation method for Jelinski-Moranda model

Jing Wei Liu; Yu Biao Hu; Xiao Ling Wang; Mei Zhi Xu

Novel nonlinear least square parameter estimation method for Jelinski-Moranda model

Jing Wei Liu^*
, Yu Biao Hu
, Xiao Ling Wang
, Mei Zhi Xu

^*此作品的通讯作者

数学科学学院

Beijing Aerospace Automatic Control Institute
Tsinghua University

科研成果: 期刊稿件 › 文章 › 同行评审

2 引用（Scopus）

摘要

A novel nonlinear least square parameter estimation (LogLSE) method for Jelinski-Moranda (J-M) model of software reliability was proposed. Developing an equivalent curve fitting function with traditional J-M least square, the formulae of the new nonlinear least square (NLS) parameters estimation were derived. The experimental results on standard software reliability failure data-Naval Tactical Data System (NTDS) and three datasets used by J. D. Musa with Newton-Raphson method for parameter estimation demonstrate that LogLSE is superior to maximum likelihood estimation (MLE) and least square estimation (LSE).

源语言	英语
页（从-至）	4791-4794
页数	4
期刊	Xitong Fangzhen Xuebao / Journal of System Simulation
卷	20
期	18
出版状态	已出版 - 20 9月 2008

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abstract = "A novel nonlinear least square parameter estimation (LogLSE) method for Jelinski-Moranda (J-M) model of software reliability was proposed. Developing an equivalent curve fitting function with traditional J-M least square, the formulae of the new nonlinear least square (NLS) parameters estimation were derived. The experimental results on standard software reliability failure data-Naval Tactical Data System (NTDS) and three datasets used by J. D. Musa with Newton-Raphson method for parameter estimation demonstrate that LogLSE is superior to maximum likelihood estimation (MLE) and least square estimation (LSE).",

keywords = "Failure data, Maximum likelihood estimation, Nonlinear least squares, Reliability estimation, Software",

author = "Liu, \{Jing Wei\} and Hu, \{Yu Biao\} and Wang, \{Xiao Ling\} and Xu, \{Mei Zhi\}",

year = "2008",

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T1 - Novel nonlinear least square parameter estimation method for Jelinski-Moranda model

AU - Liu, Jing Wei

AU - Hu, Yu Biao

AU - Wang, Xiao Ling

AU - Xu, Mei Zhi

PY - 2008/9/20

Y1 - 2008/9/20

N2 - A novel nonlinear least square parameter estimation (LogLSE) method for Jelinski-Moranda (J-M) model of software reliability was proposed. Developing an equivalent curve fitting function with traditional J-M least square, the formulae of the new nonlinear least square (NLS) parameters estimation were derived. The experimental results on standard software reliability failure data-Naval Tactical Data System (NTDS) and three datasets used by J. D. Musa with Newton-Raphson method for parameter estimation demonstrate that LogLSE is superior to maximum likelihood estimation (MLE) and least square estimation (LSE).

AB - A novel nonlinear least square parameter estimation (LogLSE) method for Jelinski-Moranda (J-M) model of software reliability was proposed. Developing an equivalent curve fitting function with traditional J-M least square, the formulae of the new nonlinear least square (NLS) parameters estimation were derived. The experimental results on standard software reliability failure data-Naval Tactical Data System (NTDS) and three datasets used by J. D. Musa with Newton-Raphson method for parameter estimation demonstrate that LogLSE is superior to maximum likelihood estimation (MLE) and least square estimation (LSE).

KW - Failure data

KW - Maximum likelihood estimation

KW - Nonlinear least squares

KW - Reliability estimation

KW - Software

UR - https://www.scopus.com/pages/publications/54049102478

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SN - 1004-731X

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JO - Xitong Fangzhen Xuebao / Journal of System Simulation

JF - Xitong Fangzhen Xuebao / Journal of System Simulation

IS - 18

ER -

Novel nonlinear least square parameter estimation method for Jelinski-Moranda model

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