Parametric likelihood inference and goodness-of-fit for dependently left-truncated data, a copula-based approach

DOI10.1007/s00362-017-0947-zzbMath1437.62180OpenAlexW2753701780MaRDI QIDQ151564

Chi-Hung Pan, Takeshi Emura, Chi-Hung Pan, Takeshi Emura

Publication date: 4 September 2017

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-017-0947-z

zbMATH Keywords

reliabilitysurvival analysisWeibull distributionleft-truncationNewton-Raphson algorithmgoodness-of-fit testbivariate life distribution

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Bayesian inference (62F15) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Applications of statistics in engineering and industry; control charts (62P30) Reliability and life testing (62N05)

Related Items (9)

Estimation of the Mann-Whitney effect in the two-sample problem under dependent censoring ⋮ U-Statistics for left truncated and right censored data ⋮ Unnamed Item ⋮ Cox regression model under dependent truncation ⋮ Model diagnostic procedures for copula-based Markov chain models for statistical process control ⋮ Likelihood-based analysis of doubly-truncated data under the location-scale and AFT model ⋮ depend.truncation ⋮ Goodness-of-fit test of copula functions for semi-parametric univariate time series models ⋮ Conditional independence test of failure and truncation times: essential tool for method selection

Uses Software

• R
• VineCopula

Cites Work

• Unnamed Item
• Unnamed Item
• Maximum likelihood estimation for a special exponential family under random double-truncation
• Nonparametric maximum likelihood estimation for dependent truncation data based on copulas
• An algorithm for estimating survival under a copula-based dependent truncation model
• Semiparametric inference for an accelerated failure time model with dependent truncation
• Testing quasi-independence for truncation data
• Empirical copulas for consecutive survival data
• Multivariate normal distribution approaches for dependently truncated data
• Robust inference for the stress-strength reliability
• Parametric families of multivariate distributions with given margins
• A goodness-of-fit test for parametric models based on dependently truncated data
• Derivatives and Fisher information of bivariate copulas
• Copula identifiability conditions for dependent truncated data model
• An introduction to copulas.
• Survival analysis. Techniques for censored and truncated data.
• Accurate higher-order likelihood inference on \(P(Y<X)\)
• Prediction of remaining life of power transformers based on left truncated and right censored lifetime data
• Bivariate quantile residual life: a characterization theorem and statistical properties
• Estimating extreme quantiles under random truncation
• A copula-based approach to account for dependence in stress-strength models
• Estimation and Model Selection for Left-truncated and Right-censored Lifetime Data with Application to Electric Power Transformers Analysis
• Practical methods for competing risks data: A review
• Testing Markovianity in the three-state progressive model via future-past association
• Testing the assumption of independence of truncation time and failure time
• Estimating survival under a dependent truncation
• Nonparametric Estimation from Cross-Sectional Survival Data
• Semiparametric Marginal Regression Analysis for Dependent Competing Risks Under an Assumed Copula
• Advanced Calculus with Applications in Statistics
• Impact of dependent left truncation in semiparametric competing risks methods: A simulation study
• Fitting competing risks with an assumed copula
• A copula-graphic estimator for the conditional survival function under dependent censoring
• Testing Quasi-Independence of Failure and Truncation Times via Conditional Kendall's Tau
• Estimating a distribution function with truncated data

This page was built for publication: Parametric likelihood inference and goodness-of-fit for dependently left-truncated data, a copula-based approach