A stationary Weibull process and its applications
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Publication:6063288
DOI10.1080/02664763.2022.2073585OpenAlexW4280616977MaRDI QIDQ6063288
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Publication date: 7 November 2023
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503463
exponential distributionWeibull distributionmaximum likelihood estimatorsminification processmaximum likelihood predictor
Estimation in multivariate analysis (62H12) Parametric hypothesis testing (62F03) Point estimation (62F10) Statistics (62-XX)
Cites Work
- Marshall-Olkin bivariate Weibull distributions and processes
- Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm
- A characterization of the Pareto process among stationary stochastic processes of the form \(X_ n=c\,\min (X_{n-1},Y_ n)\)
- Bayes estimation for the Marshall-Olkin bivariate Weibull distribution
- Estimation and Hypothesis Testing for the Parameters of a Bivariate Exponential Distribution
- Semi-Pareto processes
- On a solution of the optimal stopping problem for processes with independent increments
- Simulation of weibull and gamma autoregressive stationary process
- Pareto processes
- An exponential Markovian stationary process
- Autoregressive logistic processes
- Logistic processes involving markovian minimization
- Phase-Type Distributions and Optimal Stopping for Autoregressive Processes
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