ON REGRESSION TECHNIQUES FOR ESTIMATING THE PARAMETERS OF WEIBULL CUMULATIVE DISTRIBUTIONS.

Abstract

A regression technique for estimating Weibull scale and shape parameters is introduced and experimentally investigated. The derivation involves maximizing the likelihood function of a set of normal density functions which give the probabilities of sub fi items failing until time ti. The estimation technique was evaluated using simulated failure data and the estimators were found to be optimal according to Kolmogorov-Smirnov tests. When compared with the Harter-Moore MLE iteration technique the regression method was 145 times faster and yielded Kolmogorov-Smirnov values 26 percent lower. Of 1100 estimations only one could not be accepted at the .20 confidence level as having come from the failure data. The method is well suited for small computers such as the IBM 1620 and may be employed to analyze incomplete or censored samples of failure data. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1965
Accession Number
AD0628336

Entities

People

  • David Ian Gross

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computers
  • Estimators
  • Iterations
  • Mathematics
  • Measurement Transportation Algorithms
  • Normal Density Functions
  • Optimal Estimators
  • Probability
  • Statistical Algorithms

Readers

  • Regression Analysis.