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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), pp. 1476-1484. (doi:10.1175/1520-0450(2001)040<1476:EOWSDU>2.0.CO;2).

Record type: Article

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.

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Published date: 2001
Organisations: Statistics

Identifiers

Local EPrints ID: 29964
URI: http://eprints.soton.ac.uk/id/eprint/29964
ISSN: 1520-0450
PURE UUID: c661e507-9a8c-43db-91ab-3f87befa941f

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Date deposited: 11 May 2006
Last modified: 17 Jul 2017 15:56

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Contributors

Author: Wan-Kai Pang
Author: Marvin D. Troutt

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