Approximate Analytical Method of Maximum Likelihood Estimation of Weibull Distribution
- DOI
- 10.2991/978-94-6463-042-8_97How to use a DOI?
- Keywords
- Approximate Analytical Method; Perturbative Method; Artificial Parameter; Maximum Likelihood Estimation
- Abstract
Weibull distribution is commonly applied in survival analysis and reliability analysis, whose shape and scale parameters are most commonly estimated by maximum likelihood estimation and related numerical methods. In this paper, by introducing an artificial parameter and then using the perturbative method, for the first time in the statistics literature, we conveniently obtain approximate analytical formulas of maximum likelihood estimates of the parameters in Weibull distributions, which are important complements to those tedious and unreliable numerical methods. Monte-Carlo simulations show that the approximate analytical method proposed in this paper is fairly feasible and accurate. Using the similar method, we can also obtain the approximate analytical formulas of maximum likelihood estimates in many other statistical problems.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tian Ye AU - He Heping AU - Zhang Yu PY - 2022 DA - 2022/12/29 TI - Approximate Analytical Method of Maximum Likelihood Estimation of Weibull Distribution BT - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022) PB - Atlantis Press SP - 674 EP - 680 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-042-8_97 DO - 10.2991/978-94-6463-042-8_97 ID - Ye2022 ER -