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).

Download

Full text not available from this repository.

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
ePrint ID: 29964
Date Deposited: 11 May 2006
Last Modified: 27 Mar 2014 18:18
URI: http://eprints.soton.ac.uk/id/eprint/29964

Actions (login required)

View Item View Item