{"title":"基于隐马尔可夫模型的农产品价格数据建模","authors":"George Joshni, Thomas Seemon","doi":"10.12785/IJCTS/060103","DOIUrl":null,"url":null,"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.","PeriodicalId":373764,"journal":{"name":"International Journal of Computational and Theoretical Statistics","volume":"187 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling of Agricultural Price Data Using Hidden Markov Model\",\"authors\":\"George Joshni, Thomas Seemon\",\"doi\":\"10.12785/IJCTS/060103\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":373764,\"journal\":{\"name\":\"International Journal of Computational and Theoretical Statistics\",\"volume\":\"187 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computational and Theoretical Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12785/IJCTS/060103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational and Theoretical Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12785/IJCTS/060103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling of Agricultural Price Data Using Hidden Markov Model
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.