Asymptotic properties of estimators in a binomial reliability growth model and its continuous-time analog

DOI10.1016/0378-3758(92)90120-HzbMath0746.62024MaRDI QIDQ1193937

Gouri K. Bhattacharyya, Jayanta K. Ghosh

Publication date: 27 September 1992

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

information matrixconsistencyasymptotic normalityTaylor expansionnonhomogeneous Poisson processmaximum likelihood estimatorsreliability growthcontinuous-time growth modeldiscrete growth modelnonhomogenoeus binomial modelpseudo- likelihoodWeibull intensity

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Reliability and life testing (62N05)

Related Items (1)

Non-standard asymptotics in an inhomogeneous gamma process

Cites Work

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• Estimating the intensity function of a weibull process at the current time: failure truncated case
• Properties of continuous analog estimators for a discrete reliability-growth model
• Confidence Interval Procedures for the Weibull Process with Applications to Reliability Growth
• Maximum likelihood estimation in a class of nonregular cases
• Inferences on the Parameters and Current System Reliability for a Time Truncated Weibull Process
• Some Results on Inference for the Weibull Process

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