Bootstrap estimation for the β distribution of repeated measurement data

Hong Hua Lin*, Feng Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Uniform expression of the probability distribution of repeated measurement data by bounded β(g,h) distribution is recommended. Two kinds of estimation methods for the β distribution parameters according to small sized samples are presented. They are respectively the method of approximation boundary and the method of approximation shape. Using the bootstrap method to estimate the mean and standard deviation or skewness and kurtosis respectively, and then based on their relation the parameter estimations-(ĝ, ĥ) are obtained. The Levenberg-Marquardt method and genetic method are introduced to solve the nonlinear functions and check the results for each other, considering the large overlay range of (ĝ, ĥ). Calculation program (including simulate verification) using Matlab are made, so that it can be easily realized on the computer.

Original languageEnglish
Pages (from-to)947-951
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume24
Issue number11
Publication statusPublished - Nov 2004

Keywords

  • Bootstrap method
  • Error distribution
  • Genetic algorithm
  • Uniform expression method
  • β distribution

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