Mathematical and statistical software

Introducing the IBM SPSS Modeler, this book guides readers through data mining processes and presents relevant statistical methods.

This textbook provides an introduction to the free software Python and its use for statistical data analysis.

This book focuses on statistical methods for the analysis of discrete failure times.

This textbook introduces the vast array of features and powerful mathematical functions of Mathematica using a multitude of clearly presented examples and worked-out problems.

This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvagar, Lofoten, Norway, in May 2014.

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player.

This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning.

This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014.

This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields.

This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio.

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists.

For over two decades, this comprehensive manual has been the standard introduction and complete reference for writing articles and books containing mathematical formulas.

This is the first book to show the capabilities of Microsoft Excel to teach engineering statistics effectively.

The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.

?

A unique point of this book is its low threshold, textually simple and at the same time full of self-assessment opportunities.

This work introduces a new method for analysing measured signals: nonlinear mode decomposition, or NMD.

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software.

This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis.

These are the proceedings of the 22nd International Conference on Domain Decomposition Methods, which was held in Lugano, Switzerland.

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing).

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis.

This is the first numerical analysis text to use Sage for the implementation of algorithms and can be used in a one-semester course for undergraduates in mathematics, math education, computer science/information technology, engineering, and physical sciences.

This text covers topics in algebraic geometry and commutative algebra with a strong perspective toward practical and computational aspects.

The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas.

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.

Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps.

This book is a complete introduction to the power of R for marketing research practitioners.

This book is a comprehensive introduction to financial modeling that teaches advanced undergraduate and graduate students in finance and economics how to use R to analyze financial data and implement financial models.

This book provides new insights on the study of global environmental changes using the ecoinformatics tools and the adaptive-evolutionary technology of geoinformation monitoring.

This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively.

This Festschrift in honour of Paul Deheuvels' 65th birthday compiles recent research results in the area between mathematical statistics and probability theory with a special emphasis on limit theorems.

The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments.

Unique features of the book involve the following.

"e;We live in the age of data.

This is the first book to show the capabilities of Microsoft Excel to teach business statistics effectively.

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 volume compiles the major results of conference participants from the "e;Third International Conference in Network Analysis"e; held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups.

This book features 13 papers presented at the Fifth International Symposium on Recurrence Plots, held August 2013 in Chicago, IL.

This book provides an introduction to multistate event history analysis.

This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate.

Practical LaTeX covers the material that is needed for everyday LaTeX documents.

This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R.

Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering.

Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering.

The book presents a comprehensive vision of the impact of ICT on the contemporary city, heritage, public spaces and meta-cities on both urban and metropolitan scales, not only in producing innovative perspectives but also related to newly discovered scientific methods, which can be used to stimulate the emerging reciprocal relations between cities and information technologies.

Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text.

The objective of this book is to compare the statistical properties of penalty and non-penalty estimation strategies for some popular models.

Recent achievements in hardware and software developments have enabled the introduction of a revolutionary technology: in-memory data management.

This is the first book to show the capabilities of Microsoft Excel to teach engineering statistics effectively.