Some Further Issues Concerning Likelihood Inference for Left Truncated and Right Censored Lognormal Data

DOI10.1080/03610918.2012.703749zbMath1333.62229OpenAlexW1981345389MaRDI QIDQ5417932

Debanjan Mitra, Narayanaswamy Balakrishnan

Publication date: 23 May 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.703749

zbMATH Keywords

EM algorithmright censoringmaximum likelihood estimatorslognormal distributionasymptotic variancesleft truncationlifetime datamissing information principleparametric bootstrap confidence intervals

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Censored data models (62N01) Bootstrap, jackknife and other resampling methods (62F40) Estimation in survival analysis and censored data (62N02)

Related Items (5)

Bayesian inference of Weibull distribution based on left truncated and right censored data ⋮ Influential measures on log-normal model for left-truncated and case-k interval censored data with time-dependent covariate ⋮ U-Statistics for left truncated and right censored data ⋮ Estimation and Model Selection for Left-truncated and Right-censored Lifetime Data with Application to Electric Power Transformers Analysis ⋮ Likelihood analysis and stochastic EM algorithm for left truncated right censored data and associated model selection from the Lehmann family of life distributions

Cites Work

• Estimation of parameters from progressively censored data using EM algorithm
• Left truncated and right censored Weibull data and likelihood inference with an illustration
• Prediction of remaining life of power transformers based on left truncated and right censored lifetime data
• Likelihood inference for lognormal data with left truncation and right censoring with an illustration
• The EM Algorithm and Extensions, 2E
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Some Further Issues Concerning Likelihood Inference for Left Truncated and Right Censored Lognormal Data