1. Bootstrap confidence interval estimation on geometric process models for lifetime data analysis.
- Author
-
Awalluddin, A. S., Astuti, N. A., Cahyandari, R., and Wahyuni, I.
- Subjects
- *
GEOMETRIC modeling , *CONFIDENCE intervals , *STATISTICAL bootstrapping , *GEOMETRIC distribution , *DATA analysis , *DATA distribution - Abstract
The geometric process is one of the renewal processes in the observation systems or components in the life time data analysis. This paper aims to introduce a geometric process model in the life test analysis under normal test conditions by determining the estimation of model parameters. The assumptions of data distribution used here are exponential and Weibull distribution, and the parameter estimation method used is maximum likelihood estimation (MLE). Confidence Interval (CI) estimation for each distribution uses CI percentile bootstrap. Estimation algorithms are made for the two distribution models that estimate parameter for both distribution models and geometric process ratio Simulations were carried out to estimate the CI selected from the two models based on the root mean standard error (RMSE) value. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF