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Follow on Google News | Nonlinear Time Series: Theory, Methods and Applications with R ExamplesThis text emphasizes nonlinear models for a course in time series analysis.
By: CRC Press Features: Describes the major statistical techniques for inferring model parameters, with a focus on the MLE and QMLE Introduces concepts of nonparametric statistics, including smoothing splines Covers HMM models, including Gaussian linear, switching Markovian, and nonlinear state space models Present direct likelihood inference techniques and the EM algorithm Uses R for numerical examples and provides a dedicated R package Solutions manual available upon qualifying course adoption For more information on this new title, please visit http://www.crcpress.com/ ISBN 9781466502253, January 6, 2014, 551pp End
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