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{ "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/48/221/959/148221959X_b.jpg", "price_data" : { "retail_price" : "140.00", "online_price" : "140.00", "our_price" : "140.00", "club_price" : "140.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
State-Space Methods for Time Series Analysis|Jose Casals

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.

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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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