Nonparametric estimation of the shape function in a Gamma process for degradation data
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Publication:3636243
DOI10.1002/cjs.10003zbMath1170.62027OpenAlexW2028610091MaRDI QIDQ3636243
Publication date: 30 June 2009
Published in: Canadian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/cjs.10003
empirical processgreatest convex minorantprofile likelihoodpseudo-likelihoodgamma processpool adjacent violators algorithm
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
Related Items (9)
Bayesian Inferences for Panel Count Data and Interval-Censored Data with Nonparametric Modeling of the Baseline Functions ⋮ A time-discrete and zero-adjusted gamma process model with application to degradation analysis ⋮ Failure Time of Non Homogeneous Gamma Process ⋮ Optimal design for constant-stress accelerated degradation test based on gamma process ⋮ Modeling of degradation data via Wiener stochastic process based on acceleration factor constant principle ⋮ Considering greenhouse gas emissions in maintenance optimisation ⋮ Degradation data analysis based on gamma process with random effects ⋮ Inference for constant-stress accelerated degradation test based on gamma process ⋮ On degradation-based imperfect repair and induced generalized renewal processes
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- Survival in dynamic environments
- Accelerated degradation models for failure based on geometric Brownian motion and gamma processes
- Two estimators of the mean of a counting process with panel count data.
- Weak convergence and empirical processes. With applications to statistics
- Fitting the variance-gamma model to financial data
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