A non-parametric hidden Markov model for climate state identification
Hidden Markov models (HMMs) can allow for the varying wet and dry cycles in the climate without the need to simulate supplementary climate variables. The fitting of a parametric HMM relies upon assumptions for the state conditional distributions. It is shown that inappropriate assumptions abou...
Main Authors: | M. F. Lambert, J. P. Whiting, A. V. Metcalfe |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2003-01-01
|
Series: | Hydrology and Earth System Sciences |
Online Access: | http://www.hydrol-earth-syst-sci.net/7/652/2003/hess-7-652-2003.pdf |
Similar Items
-
Radar working-state identification using the hidden Markov model
by: Wei Zhang, et al.
Published: (2019-10-01) -
Applying Hidden Markov Model and Observable Markov Model for Audio Content Identification
by: Gen-Kai Huang, et al.
Published: (2007) -
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
by: Stephen Adams, et al.
Published: (2016-01-01) -
Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification
by: Baribault, Carl
Published: (2009) -
Mobile Application Identification based on Hidden Markov Model
by: Yang Xinyan, et al.
Published: (2018-01-01)