{"title":"Randall L Eubank","description":"\u003cp\u003eDelve into Randall L. Eubank's thrilling world, blending action, suspense, and political intrigue. Perfect for fans of Robert Ludlum or Vince Flynn, discover gripping tales of espionage and high-stakes adventure.\u003c\/p\u003e","products":[{"product_id":"kalman-filter-primer-book-randall-l-eubank-9780824723651","title":"A Kalman Filter Primer","description":"This text provides a self-contained, no frills, mathematically rigorous derivation from first principles of all basic Kalman filter recursions. This approach relies on a pared-down version of more general state-space models found most often in the literature. Such simplification saves notational complexity without sacrificing conceptual understanding. The rigor found in the book ensures a fundamental understanding of how the Kalman filter actually works, which builds confidence for those employing the filter in their research and writing code to implement it in practice. The author provides implementations of the Kalman filter in Java available for download from his Web site.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50763246338321,"sku":"CIN0824723651G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52522358931729,"sku":"NLS9780824723651","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0824723651.jpg?v=1750979542"},{"product_id":"nonparametric-regression-and-spline-smoothing-book-randall-l-eubank-9780367579210","title":"Nonparametric Regression and Spline Smoothing","description":"Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.","brand":"WoB","offers":[{"title":"US \/ NEW \/ INGRAM","offer_id":51001595429137,"sku":"NIN9780367579210","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52138947870993,"sku":"NLS9780367579210","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0367579219.jpg?v=1751071787"},{"product_id":"nonparametric-regression-and-spline-smoothing-book-randall-l-eubank-9780824793371","title":"Nonparametric Regression and Spline Smoothing","description":"Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52133325406481,"sku":"NLS9780824793371","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53689296290065,"sku":"NIN9780824793371","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9780824793371.jpg?v=1757528924"},{"product_id":"kalman-filter-primer-book-randall-l-eubank-9780367391690","title":"A Kalman Filter Primer","description":"This text provides a self-contained, no frills, mathematically rigorous derivation from first principles of all basic Kalman filter recursions. This approach relies on a pared-down version of more general state-space models found most often in the literature. Such simplification saves notational complexity without sacrificing conceptual understanding. The rigor found in the book ensures a fundamental understanding of how the Kalman filter actually works, which builds confidence for those employing the filter in their research and writing code to implement it in practice. 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The book discusses code development in C++ and R and the use of these symbiotic languages in unison. It emphasizes that each offers distinct features that, when used in tandem, can take code writing beyond what can be obtained from either language alone.   The text begins with some basics of object-oriented languages, followed by a \"boot-camp\" on the use of C++ and R. The authors then discuss code development for the solution of specific computational problems that are relevant to statistics including optimization, numerical linear algebra, and random number generation. Later chapters introduce abstract data structures (ADTs) and parallel computing concepts. The appendices cover R and UNIX Shell programming.  Features         Includes numerous student exercises ranging from elementary to challenging Integrates both C++ and R for the solution of statistical computing problems  Uses C++ code in R and R functions in C++ programs  Provides downloadable programs, available from the authors’ website  The translation of a mathematical problem into its computational analog (or analogs) is a skill that must be learned, like any other, by actively solving relevant problems. The text reveals the basic principles of algorithmic thinking essential to the modern statistician as well as the fundamental skill of communicating with a computer through the use of the computer languages C++ and R. 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