{
"item_title" : "State-Space Methods for Time Series Analysis",
"item_author" : [" Jose Casals", "Alfredo Garcia-Hiernaux", "Miguel Jerez "],
"item_description" : "Exploring the advantages of the state-space approach, this book presents numerous computational procedures that can be applied to a previously specified linear model in state-space form. It discusses model estimation and signal extraction; describes many procedures to combine, decompose, aggregate, and disaggregate a state-space form; and covers the connection between mainstream time series models and the state-space representation. Source code, a complete user manual, and other materials related to the authors' MATLAB(R) toolbox are available on a supplementary website.",
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State-Space Methods for Time Series Analysis : Theory, Applications and Software
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Overview
Exploring the advantages of the state-space approach, this book presents numerous computational procedures that can be applied to a previously specified linear model in state-space form. It discusses model estimation and signal extraction; describes many procedures to combine, decompose, aggregate, and disaggregate a state-space form; and covers the connection between mainstream time series models and the state-space representation. Source code, a complete user manual, and other materials related to the authors' MATLAB(R) toolbox are available on a supplementary website.
This item is Non-Returnable
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Details
- ISBN-13: 9781482219593
- ISBN-10: 148221959X
- Publisher: CRC Press
- Publish Date: March 2016
- Dimensions: 9.2 x 6.2 x 0.9 inches
- Shipping Weight: 1.19 pounds
- Page Count: 298
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