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Parallel processing can be ideally suited for the solving of more complex problems in statistical computing. This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It requires a working knowledge of both the basic concepts in statistics and experience in programming.
Presents an account of popular approaches to nonparametric regression smoothing. This book discusses boundary corrections for trigonometric series estimators; asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; and practical aspects, problems and methods for confidence intervals and bands.
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