Mathematical and statistical software

This book represents the refereed proceedings of the Third International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at Claremont Graduate University in 1998.

Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "e;tools"e; that make it mostly self-contained.

This volume contains the outstanding collection of invited papers and refereed papers selected for the Second International Congress on Mathematical Software, ICMS 2006, held in Castro Urdiales, Spain, September 1-3, 2006.

This book of peer-reviewed short papers on methodological and applied statistics and demography is the third of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024), held in Bari, Italy, on June 17-20, 2024.

In many fields of modern mathematics specialised scientific software becomes increasingly important.

This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples.

This book gathers a selection of invited and contributed lectures from the European Conference on Numerical Mathematics and Advanced Applications (ENUMATH) held in Lausanne, Switzerland, August 26-30, 2013.

This textbook integrates the teaching and learning of statistical concepts with the acquisition of the Stata (version 16) software package.

Candlesticks have become a key component of platforms and charting programs for financial trading.

This handy reference book detailing the intricacies of R covers version 4.

"e;This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist.

Das Buch bietet eine Einführung in Wahrscheinlichkeitsmodelle und die Schätzung solcher Modelle auf der Grundlage von Beobachtungen.

Ob Naturwissenschaftler, Mathematiker, Ingenieur oder Datenwissenschaftler - mit MATLAB haben Sie ein mächtiges Tool in der Hand, das Ihnen die Arbeit mit Ihren Daten erleichtert.

Sharpening Your Advanced SAS Skills presents sophisticated SAS programming techniques, procedures, and tools, such as Proc SQL, hash tables, and SAS Macro programming, for any industry.

The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories and methods can be addressed using the open source, multi-platform R tool.

Clifford algebras are at a crossing point in a variety of research areas, including abstract algebra, crystallography, projective geometry, quantum mechanics, differential geometry and analysis.

Hands-on guide to the R system for data analysis for scientists, students and practising statisticians.

The matrix laboratory interactive computing environment-MATLAB-has brought creativity to research in diverse disciplines, particularly in designing and programming experiments.

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Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018.

The purpose of this book is not only to revisit the "e;significance test controversy,"e;but also to provide a conceptually sounder alternative.

Key FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsWhat you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is forIf you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you.

The theme of the meeting was "e;Statistical Methods for the Analysis of Large Data-Sets"e;.

Learn the essentials of the JMP Scripting Language with this beginner's guide.

Advance your knowledge of operations research and socialgood!

Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research.

An accessible primer on how to create effective graphics from dataThis book provides students and researchers a hands-on introduction to the principles and practice of data visualization.

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing.

Computational complexity is one of the most beautiful fields of modern mathematics, and it is increasingly relevant to other sciences ranging from physics to biology.

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics.

Start your journey with SAS.

Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniquesAbout This BookGain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packagesUnderstand how to apply useful data analysis techniques in R for real-world applicationsAn easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysisWho This Book Is ForThis book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages.

This book was written to provide guidance for those who need to apply statistical methods for practical use.

This book should illustrate the impact of collaborations between mathematics and industry.

This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation.

This book depicts a wide range of situations in which there exist finite form representations for the Meijer G and the Fox H functions.

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain.

Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience.

This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021.

This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields.

A hands-on guide to using Excel in the business context First published in 2012, Using Excel for Business and Financial Modelling contains step-by-step instructions of how to solve common business problems using financial models, including downloadable Excel templates, a list of shortcuts and tons of practical tips and techniques you can apply straight away.

Must-have study guide for the SAS(R) Certified Statistical Business Analyst Using SAS(R)9: Regression and Modeling exam!

This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018.

Tough Test Questions?

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software.