Kategoria BISAC: Mathematics >> Probability & Statistics - Multivariate Analysis

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to...

Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with...

This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multiway component techniques. Multiway analysis is a specialized branch of the larger field of multivariate statistics that extends the standard methods for two-way data, such as component analysis, factor analysis, cluster analysis, correspondence analysis, and multidimensional scaling to multiway data. Applied Multiway Data Analysis presents a unique, thorough, and authoritative treatment...

On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful to identify latent, or unobserved, subgroups in a population, where individuals' subgroup membership is inferred from their responses on a set of observed variables. Latent Class and Latent Transition Analysis provides a...

The text itself:
In this second edition, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, examples and applications from diverse areas, and most importantly, an explanation of intuition and ideas behind the statistical methods. To quote from the preface, "it is only when a student develops a feel or intuition for statistics that she or he is...

Linear models courses are often presented as either theoretical or applied. Consequently, students may find themselves either proving theorems or using high-level procedures like PROC GLM to analyze data. There exists a gap between the derivation of formulas and analyses that hide these formulas behind attractive user interfaces. This book bridges that gap, demonstrating theory put into practice.

Concepts presented in a theoretical linear models course are often trivialized in applied linear models courses by the facility of high-level SAS procedures like PROC MIXED and PROC REG...

A comprehensive overview of multivariate data and analysis

Providing an introduction to the subject of multivariate data analysis without delving deeply into underlying theory and concepts, An Introduction to Multivariate Data is an excellent resource for undergraduate statistics courses as well as for professionals who require an understanding of statistical techniques for analyzing their own data sets. Focused on real-world application, the book includes sample exercises in each chapter to firmly cement the concepts covered. Exercises range from simple problems that...

Find the right algorithm for your image processing application

Exploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and computer vision. The author covers all facets geometric, statistical, and computational of the methods. He looks at how the numerical algorithms relate to one another through underlying ideas, compares the strengths...

Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and...

This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.
Real life examples are used...