Estimation of wind speed distribution using Markov chain Monte Carlo techniques
Pang, Wan-Kai, Forster, Jonathan J. and Troutt, Marvin D. (2001) Estimation of wind speed distribution using Markov chain Monte Carlo techniques. Journal of Applied Meteorology, 40, (8), 1476-1484. (doi:10.1175/1520-0450(2001)040<1476:EOWSDU>2.0.CO;2).
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Description/Abstract
The Weibull distribution is the most commonly used statistical distribution for describing wind speed data. Maximum likelihood has traditionally been the main method of estimation for Weibull parameters. In this paper, Markov chain Monte Carlo techniques are used to carry out a Bayesian estimation procedure using wind speed data obtained from the Observatory of Hong Kong. The method is extremely flexible. Inference for any quantity of interest is routinely available, and it can be adapted easily when data are truncated.
| Item Type: | Article |
|---|---|
| ISSNs: | 1520-0450 (print) |
| Related URLs: | |
| Subjects: | Q Science > QA Mathematics H Social Sciences > HA Statistics |
| Divisions: | University Structure - Pre August 2011 > School of Mathematics > Statistics |
| Item ID: | 29964 |
| Date Deposited: | 11 May 2006 |
| Last Modified: | 01 Jun 2011 08:58 |
| Contributors: | Pang, Wan-Kai (Author) Forster, Jonathan J. (Author) Troutt, Marvin D. (Author) |
| Date: | 2001 |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/29964 |
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