Multivariate Dependent Renewal Processes.

Abstract

A new class of reliability point-process models for dependent components is introduced. The dependence is expressed through a regression, following a form suggested for survival data analysis involving the current life-length of the components. After formulating the current-life process as a Markov process with stationary transitions and stating some general results on asymptotic behavior, the authors describe the stationary distributions in some bivariate examples. Finally, they discuss statistical inference for the new models, exhibiting and justifying full- and partial-likelihood methods for their analysis.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA128818

Entities

People

  • Eric Slud

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Air Force
  • Data Analysis
  • Data Science
  • Information Science
  • Markov Processes
  • Maryland
  • Mathematics
  • New York
  • Probability
  • Random Variables
  • Reliability
  • Scientific Research
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Universities

Fields of Study

  • Mathematics

Readers

  • Artificial Intelligence
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms