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Basic Elements of Computational Statistics

Basic Elements of Computational Statistics

Ostap Okhrin / Wolfgang Karl Härdle / Yarema Okhrin

122,74 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2017
Materia
Probabilidad y estadística
ISBN:
9783319553351
122,74 €
IVA incluido
Disponible

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This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs.The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various mathematical roots of multivariate techniques.The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web.  QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.

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Otros libros del autor

  • Basic Elements of Computational Statistics
    Ostap Okhrin / Wolfgang Karl Hardle / Yarema Okhrin
    This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the ...
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