An Algorithm for the Computation of Generalized Likelihood or Self-Critical Estimators for Binary Data.

Abstract

This paper describes the computational algorithms for computing generalized likelihood estimators for parametric proportional hazards models. Subroutine BINARY is an implementation of the self-critical estimation procedure of Paulson, Presser and Lawrence (1983). The logistic, Gaussian or Type I extreme value distribution may be selected as tolerance distribution. Estimates are expressed in location-scale form on entry and exit, but results may be printed out in regression form, location-scale form, or in both forms. It is possible to hold location parameters constant during the estimation procedure. Estimation is accomplished by a Newton-Raphson method. Keywords: FORTRAN; Mathematical Models.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA178545

Entities

People

  • A. S. Paulson
  • T. A. Delahanty

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computers
  • Covariance
  • Data Science
  • Distribution Functions
  • Estimators
  • Gaussian Distributions
  • Information Science
  • Iterations
  • Models
  • Normal Distribution
  • Plastic Explosives
  • Precision
  • Procedures (Computers)
  • Self Assembly
  • Standards

Fields of Study

  • Mathematics

Readers

  • Database Systems and Applications
  • Regression Analysis.
  • Statistical inference.