Modeling of Agricultural Price Data Using Hidden Markov Model

dc.contributor.author	Joshni, George
dc.contributor.author	Seemon, Thomas
dc.date.accessioned	2019-04-29T09:55:48Z
dc.date.available	2019-04-29T09:55:48Z
dc.date.issued	2019-05-01
dc.identifier.uri	https://journal.uob.edu.bh:443/handle/123456789/3472
dc.description.abstract	In this paper, we explore the application of hidden Markov model (HMM) in the modeling of agricultural price data. Normal hidden Markov model is fitted and compared with univariate autoregressive moving average (ARMA) model. The parameters of the model are estimated using EM algorithm and the sequence of hidden states are obtained based on the best fitted model.	en_US
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Markov Process	en_US
dc.subject	Transition Probability Matrix	en_US
dc.subject	Stationary Distribution	en_US
dc.subject	Decoding	en_US
dc.title	Modeling of Agricultural Price Data Using Hidden Markov Model	en_US
dc.identifier.doi	http://dx.doi.org/10.12785/ijcts/060103
dc.volume	Volume 6	en_US
dc.issue	Issue 1	en_US
dc.contributor.authorcountry	India	en_US
dc.contributor.authoraffiliation	Department of Statistics, St.Thomas College Palai, Kottayam, Kerala , India.	en_US
dc.source.title	International Journal of Computational and Theoretical Statistics	en_US
dc.abbreviatedsourcetitle	IJCTS	en_US