Mathematical and statistical software

This book covers the basics of numerical methods.

This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-PM.

In den letzten Jahren hat sich gerade die Zeit-Frequenz-Analyse mit der Signaldarstellung in Frames, der Kurzzeit-Fourier-Transformation, der Wavelet-Transformation und der Wigner-Ville-Verteilung zu einem der wichtigsten Gebiete in der Signalverarbeitung entwickelt.

Enhance your SAS data-wrangling skills with high-precision and parallel data manipulation using the DS2 programming language.

Learn window function foundational concepts through a cookbook-style approach, beginning with an introduction to the OVER() clause, its various configurations in terms of how partitions and window frames are created, and how data is sorted in the partition so that the window function can operate on the partition data sets.

To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject.

The theory of U-statistics goes back to the fundamental work of Hoeffding [1], in which he proved the central limit theorem.

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R.

Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas.

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences.

Practical numerical methods for solving differential equations are illustrated in the increasingly popular open source language R.

"e;Gratzer's book is a solution.

This research monograph utilizes exact and Monte Carlo permutation statistical methods to generate probability values and measures of effect size for a variety of measures of association.

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability.

The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work.

This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics.

This work is a collection of front-end research papers on data fusion and perceptions.

Beginning R, Second Edition is a hands-on book showing howto use the R language, write and save R scripts, read in data files, and writecustom statistical functions as well as use built in functions.

This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics.

This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach.

This book is a self-teaching guide to the SPSS for Windows computer package.

Each chapter will consist of basic statistical theory, simple examples of S-PLUS code, more complex examples of S-PLUS code, and exercises.

This book systematically investigates the Mars entry problem from the perspectives of deterministic optimization, uncertainty optimization, and guidance.

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques.

MatLab, Third Edition is the only book that gives a full introduction to programming in MATLAB combined with an explanation of the software's powerful functions, enabling engineers to fully exploit its extensive capabilities in solving engineering problems.

A guide for MATLAB programmers that offers a collection of standards and guidelines for creating MATLAB code that will be easy to understand.

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment.

Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods.

There has been dramatic growth in the development and application of Bayesian inference in statistics.

Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions.

Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science.

This volume contains the papers presented at the 7th International Conference on Independent Component Analysis (ICA) and Source Separation held in L- don, 9-12 September 2007, at Queen Mary, University of London.

Ideal for those wishing a deeper understanding of Mathematica programming, with software support and solutions to exercises available on the web.

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 advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.

This book shows the capabilities of Microsoft Excel in teaching business statistics effectively.

This textbook for graduate and advanced undergraduate students presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra.

Master Statistical Quality Control using JMP !

This book presents a comprehensive study of multivariate time series with linear state space structure.

This book provides practical applications of doubly classified models by using R syntax to generate the models.

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R.

This book highlights the principles of psychological assessment to help researchers and clinicians better develop, evaluate, administer, score, integrate, and interpret psychological assessments.

Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data.

Apply analytics to business problems using two very popular software tools, SAS and R.

Fast Compact Algorithms and Software for Spline Smoothing investigates algorithmic alternatives for computing cubic smoothing splines when the amount of smoothing is determined automatically by minimizing the generalized cross-validation score.