| contributor author | Pang, Wan-Kai | |
| contributor author | Forster, Jonathan J. | |
| contributor author | Troutt, Marvin D. | |
| date accessioned | 2017-06-09T14:08:00Z | |
| date available | 2017-06-09T14:08:00Z | |
| date copyright | 2001/08/01 | |
| date issued | 2001 | |
| identifier issn | 0894-8763 | |
| identifier other | ams-13034.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4148440 | |
| 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. | |
| publisher | American Meteorological Society | |
| title | Estimation of Wind Speed Distribution Using Markov Chain Monte Carlo Techniques | |
| type | Journal Paper | |
| journal volume | 40 | |
| journal issue | 8 | |
| journal title | Journal of Applied Meteorology | |
| identifier doi | 10.1175/1520-0450(2001)040<1476:EOWSDU>2.0.CO;2 | |
| journal fristpage | 1476 | |
| journal lastpage | 1484 | |
| tree | Journal of Applied Meteorology:;2001:;volume( 040 ):;issue: 008 | |
| contenttype | Fulltext | |
