Accession Number:

AD0653663

Title:

MAXIMUM-LIKELIHOOD ESTIMATION OF THE PARAMETERS OF A FOUR-PARAMETER GENERALIZED GAMMA POPULATION FROM COMPLETE AND CENSORED SAMPLES

Descriptive Note:

Revised ed.,

Corporate Author:

AEROSPACE RESEARCH LABS WRIGHT-PATTERSON AFB OH

Personal Author(s):

• Harter, H. L.

Report Date:

1967-02-01

Pagination or Media Count:

11.0

Abstract:

Consider the four-parameter generalized Gamma population with location parameter c, scale parameter a, shapepower parameter b, and power parameter p shape parameter d bp and probability density function fx c, a, b, p px - c raised to the power bp-1, exp -x - ca raised to the power pa raised to the power bp, Gamma b, where a, b, p 0 and x or c or 0. The likelihood equations for parameter estimation are obtained by equating to zero the first partial derivatives, with respect to each of the four parameters, of the natural logarithm of the likelihood function for a complete or censored sample. The asymptotic variances and covariances of the maximum- likelihood estimators are found by inverting the information matrix, whose components are the limits, as the sample size n approaches infinity, of the negatives of the expected values of the second partial derivatives of the likelihood function with respect to the parameters. The likelihood equations cannot be solved explicitly, but an iterative procedure for solving them on an electronic computer is described. The results of applying this procedure to samples from Gamma, Weibull, and half-normal populations are tabulated, as are the asymptotic variances and covariances of the maximum-likelihood estimators.

Descriptors:

• *MATHEMATICAL PREDICTION
• REPRINTS
• SAMPLING
• MATHEMATICS
• SPECIAL FUNCTIONS(MATHEMATICS)
• ITERATIONS
• TABLES(DATA)
• PROBABILITY DENSITY FUNCTIONS

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE