Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34743
Title: Estimation of wind speed distribution using Markov Chain Monte Carlo techniques
Authors: Pang, WK
Forster, JJ
Troutt, MD
Issue Date: 2001
Publisher: American Meteorological Society
Source: Journal of applied meteorology, 2001, v. 40, no. 8, p. 1476-1484 How to cite?
Journal: Journal of applied meteorology
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.
URI: http://hdl.handle.net/10397/34743
ISSN: 0894-8763 (print)
1520-0450 (online)
DOI: 10.1175/1520-0450(2001)040<1476:EOWSDU>2.0.CO;2
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