In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958,- Ro
The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focus
This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natura
This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading exper
This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to.
This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. I
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s stru
The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contai
A number of advances have taken place in panel data analysisduring the pastthree decades and it continues to be one ofthe most active areas of research. This volume contains 13significant contr
A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineerin
Together with the development of information technologies the requirements for data analysis tools have grown significantly. Due to such recent advances, as ubiquitous computing or the Internet of thi
Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often perfo
This volume provides recent research results in data analysis, classification and multivariate statistics and highlights perspectives for new scientific developments within these areas. Particular att
Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or pati
Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of intere
This BriefBook is a much extended glossary or a much condensed handbook, depending on the way one looks at it. In encyclopedic format, it covers subjects in statistics, computing, analysis, and relate
The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as fo
This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data
Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data
This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and
This book is written for students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills: data analysis, business m
This is the second edition of a highly successful first edition. It contains a considerable amount of new material.Much of the work is original to the authors. Bernard Silverman has been very s
Der zweite Band von "Datenanalyse mit Mplus" wendet sich an fortgeschrittene Anwender, die uber solides statistisches Hintergrundwissen und erste Mplus-Kenntnisse verfugen. Wie geht man mit ordinalen
This book inclusively and systematically presents the fundamental methods, models and techniques of practical application of grey data analysis, bringing together the authors’ many years of theoretica
?This volume presents new research results in data analysis and statistical modelling and offers a wealth of applications in areas such as economics and finance, education, social sciences, environmen
Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of
This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading exper
When scientists analyze datasets in a search for underlying phenomena, patterns or causal factors, their first step is often an automatic or semi-automatic search for structures in the data. Of these
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the
This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in
This is a new edition to the classic book by ggplot2 creator Hadley Wickham. ggplot2 is a data visualization package for R that helps users create data graphics, including those th
Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types
The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned,
The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked, and very few books deal with these techniq
This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in var
This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP
This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a c
This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the in
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. It includes theo
This volume contains the extended version of selected talks given at the international research workshop "Coping with Complexity: Model Reduction and Data Analysis", Ambleside, UK, August 31 – Septemb
