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  Browse All Reviews > Mathematics Of Computing (G) > Probability And Statistics (G.3) > Statistical Computing (G.3...)  
  1-10 of 57 Reviews about "Statistical Computing (G.3...)": Date Reviewed
  Parallel-and-stream accelerator for computationally fast supervised learning
Hector E., Luo L., Song P. Computational Statistics & Data Analysis 177(1): 1-12, 2022.  Type: Article

Large enterprises with massive amounts of data require reliable and efficient algorithms for exploring and forecasting trends in available supplies, user purchases, and advertisements. The scalability of the MapReduce approach is advantageous for ...

Feb 20 2023
  Excel 2019 for physical sciences statistics: a guide to solving practical problems (2nd ed.)
Quirk T., Quirk M., Horton H., Springer International Publishing, Cham, Switzerland, 2021. 264 pp.  Type: Book (978-3-030632-37-3)

This self-teaching volume belongs to a long series of similar volumes by Thomas Quirk (the main author) about the basic uses of Microsoft Excel spreadsheet software for simple statistics. This second edition covers the 2019 version of Excel, while...

Oct 31 2022
   Bringing Bayesian models to life
Hooten M., Hefley T., CRC Press, Boca Raton, FL, 2019. 573 pp.  Type: Book (978-0-367198-48-0)

We are used to classical statistics, yet in many important contemporary applications, such as the estimation of parameters in machine learning, a second branch of statistics based on Bayesian methods is very attractive. Therefore, a bo...

Aug 23 2022
   A domain theory for statistical probabilistic programming
Vákár M., Kammar O., Staton S. Proceedings of the ACM on Programming Languages 3(POPL): 1-29, 2019.  Type: Article

On the one hand, a statistical programming language is similar to a traditional programming language, but with libraries providing statistical functions. Examples are Mathematica, MATLAB, and the omnipresent R. On the other hand, proba...

Aug 6 2020
   Data exploration using example-based methods
Lissandrini M., Mottin D., Palpanas T., Velegrakis Y., Morgan&Claypool Publishers, San Rafael, CA, 2019. 164 pp.  Type: Book (978-1-681734-55-2)

This book provides a comprehensive overview and description of a broad range of search algorithms. Because the authors are experts at example-based searching methods, the book discusses the application of example-based approaches to se...

Nov 18 2019
  Introductory biostatistics (2nd ed.)
Le C., Eberly L., Wiley Publishing, Hoboken, NJ, 2016. 616 pp.  Type: Book (978-0-470905-40-1)

Le and Eberly’s Introductory biostatistics is in fact more than introductory. Not only do the authors painstakingly clarify the fundamentals of the topic, but they also provide sufficient material for an advanced under...

Apr 19 2019
  Basic elements of computational statistics
Härdle W., Okhrin O., Okhrin Y., Springer International Publishing, New York, NY, 2017. 305 pp.  Type: Book (978-3-319553-35-1)

Researchers frequently use statistics to analyze their results. Statistical analysis is a vital tool to confirm or reject hypotheses. In this context, R, one of the most famous programs used for data analysis and statistics, is a power...

Jan 24 2019
  Introduction to deep learning using R: a step-by-step guide to learning and implementing deep learning models using R
Beysolow T., Apress, New York, NY, 2017. 227 pp.  Type: Book (978-1-484227-33-6)

This is the era of machine intelligence. The domain of machine learning, and in particular deep learning, has evolved rapidly, and we have started to develop and use real-life applications from this evolution. The book serves the purpo...

Jul 11 2018
  Introduction to the new statistics: estimation, open science, and beyond
Cumming G., Calin-Jageman R., Routledge, New York, NY, 2016. 594 pp.  Type: Book (978-1-138825-52-9)

Statistics has many varied uses in society. This introductory statistics book would be of interest to undergraduate statistics students, university lecturers, and researchers. The book examines the use of statistics with regard to deve...

Aug 31 2017
  Financial analytics with R: building a laptop laboratory for data science
Bennett M., Hugen D., Cambridge University Press, New York, NY, 2016. 392 pp.  Type: Book (978-1-107150-75-1)

Billed as “a training resource for ... students and professionals,” this title is a sophisticated manual on financial data manipulation, statistics, and R programming. It is by no means for the beginner or the faint...

Jun 23 2017
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