Mathematical and statistical software

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL).

This focuses on the developing field of building probability models with the power of symbolic algebra systems.

This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cadiz (Spain) between June 11-16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid.

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields.

This book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science problems.

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

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

This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS.

This book presents recent results on positivity and optimization of polynomials in non-commuting variables.

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program.

This volume contains pioneering contributions to both the theory and practice of optimal experimental design.

This proceedings volume contains eight selected papers thatwere presented in the International Symposium in Statistics (ISS) 2015 OnAdvances in Parametric and Semi-parametric Analysis of Multivariate, TimeSeries, Spatial-temporal, and Familial-longitudinal Data, held in St.

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences:To introduce when nonparametric approaches to data analysis are appropriateTo introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each testTo introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively.

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

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.

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field.

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.