{"product_id":"hidden-markov-models-for-time-series-an-introduction-using-r-second-edition-paperback","title":"Hidden Markov Models for Time Series: An Introduction Using R, Second Edition - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eWalter Zucchini\u003c\/b\u003e (Author), \u003cb\u003eIain L. MacDonald\u003c\/b\u003e (Author), \u003cb\u003eRoland Langrock\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eHidden Markov Models for Time Series: An Introduction Using R, Second Edition\u003c\/b\u003e illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAfter presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations.\u003c\/p\u003e\u003cp\u003eFeatures\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003col\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003ePresents an accessible overview of HMMs\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eExplores a variety of applications in ecology, finance, epidemiology, climatology, and sociology\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eIncludes numerous theoretical and programming exercises\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eProvides most of the analysed data sets \u003cb\u003eonline\u003c\/b\u003e \u003c\/li\u003e \u003c\/ol\u003e\u003cp\u003eNew to the second edition\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003col\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eA total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process\u003c\/li\u003e \u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eNew case studies on animal movement, rainfall occurrence and capture-recapture data\u003c\/li\u003e \u003c\/ol\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eWalter Zucchini, Iain K. MacDonald, Roland Langrock\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 400\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.82 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 30, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":48290038808825,"sku":"9781032179490","price":111.76,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/zD-BLN7fva9781032179490.webp?v=1776276817","url":"https:\/\/bookscloud.io\/products\/hidden-markov-models-for-time-series-an-introduction-using-r-second-edition-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}