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{ "item_title" : "Advances in Complex Data Modeling and Computational Methods in Statistics", "item_author" : [" Anna Maria Paganoni", "Piercesare Secchi "], "item_description" : "The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/31/938/537/3319385372_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advances in Complex Data Modeling and Computational Methods in Statistics|Anna Maria Paganoni

Advances in Complex Data Modeling and Computational Methods in Statistics

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Overview

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

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Details

  • ISBN-13: 9783319385372
  • ISBN-10: 3319385372
  • Publisher: Springer
  • Publish Date: August 2016
  • Dimensions: 9.21 x 6.14 x 0.46 inches
  • Shipping Weight: 0.69 pounds
  • Page Count: 209

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