Basic Elements of Computational Statistics: Statistics and Computing
Autor Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrinen Limba Engleză Hardback – 10 oct 2017
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 ma
thematical 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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Specificații
ISBN-13: 9783319553351
ISBN-10: 3319553356
Pagini: 328
Ilustrații: XXI, 305 p. 97 illus., 66 illus. in color.
Dimensiuni: 160 x 241 x 24 mm
Greutate: 0.61 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Statistics and Computing
Seria Statistics and Computing
Locul publicării:Cham, Switzerland
ISBN-10: 3319553356
Pagini: 328
Ilustrații: XXI, 305 p. 97 illus., 66 illus. in color.
Dimensiuni: 160 x 241 x 24 mm
Greutate: 0.61 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Statistics and Computing
Seria Statistics and Computing
Locul publicării:Cham, Switzerland
Cuprins
The Basics of R.- Numerical Techniques.- Combinatorics and Discrete Distributions.- Univariate Distributions.- Univariate Statistical Analysis.- Basic Nonparametric Methods.- Multivariate Distributions.- Multivariate Statistical Analysis.- Random Numbers in R.- Advanced Graphical Techniques in R.- Symbols and Notations.
Recenzii
“This is an excellent book that belongs in the libraries of most of us who use statistical computing. I love this book for a number of reasons … .” (David E. Booth, Technometrics, Vol. 60 (3), 2018)
“The book deals with different tools and concepts regarding statistical analysis. … The book is intended for advanced undergraduate and even MSc students, as well as PhD student, working with different statistical techniques.” (Florin Gorunescu, zbMATH 1392.62001, 2018)
Notă biografică
Wolfgang Karl Härdle is the Ladislaus von Bortkiewicz Professor of Statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. (Center for Applied Statistics and Economics), director of the CRC-649 (Collaborative Research Center) "Economic Risk" and director of the IRTG 1792 "High Dimensional Non-stationary Time Series". He teaches quantitative finance and semi-parametric statistics. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected member of the ISI (International Statistical Institute) and advisor to the Guanghua School of Management, Peking University and a senior fellow of Sim Kee Boon Institute of Financial Economics at the Singapore Management University.
Sigbert Klinke is a postdoctoral research fellow at the Ladislaus von Bortkiewicz Chair of Statistics at Humboldt-Universität zu Berlin. He received his PhD in computational statistics from the Catholique University in Louvain-la-Neuve, Belgium. He teaches introductory statistics courses and data analytical courses for bachelor and master students in Economics and Educational Science at Humboldt-Universität zu Berlin's School of Business and Economics. His research focuses on computational and multivariate statistics and the teaching of statistics.
Bernd Rönz was a Professor of Statistics at the Institute for Statistics and Econometrics, School of Business and Economics, Humboldt University, Berlin. He taught Statistics, Computational Statistics and Generalized Linear Models. His research focused on multivariate statistics, computational statistics and generalized linear models. He previously worked as Associate Professor of Quantitative Methods for Business Decisions at the University of Dar es Salaam, Tanzania for more than two years. Furthermore, he was a Visiting Lecturer at Hosei-University Tokyo and Ritsumeikan-University Kyoto and a Visiting Fellow at the Centre for Mathematics and its Applications, School of Mathematical Sciences, The Australian National University, Canberra. He retired in 2006.
Textul de pe ultima copertă
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.
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.
Caracteristici
Covers basic mathematical, statistical and programming problems in computational statistics Addresses both univariate and multivariate statistical data analysis and applications in finance, the life sciences and other disciplines Features R sniplets in the text and computer programs on GitHub that allow all examples to be fully reproduced Provides a smooth introduction to R for statistical computing Includes supplementary material: sn.pub/extras