Spatial Data Analysis

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of

Analysis of Variance (ANOVA) is a statistical technique used in a number of chemical areas including the food industry. This handbook is a highly readable guide to the uses of the very important techn

In this second edition of his best-selling book, Data Structures and Algorithm Analysis in C, Mark Allen Weiss, continues to refine and enhance his innovative approach to algorithms and data structure

A clear and systematic treatment of time series of data, regular and chaotic, found in nonlinear systems. The text leads readers from measurements of one or more variables through the steps of buildin

Not another O.J. Simpson trial exposT, but a new edition of the standard reference interpreting discrete population genetic data (for example, DNA profiles). Weir illustrates concepts in estimating f

Data measured as angles or two-dimensional orientations are found almost everywhere in science. They commonly arise in biology, geography, geophysics, medicine, meteorology and oceanography, and many other areas. Examples of such data include departure directions of birds from release points, fracture plane orientations, the directional movement of animals after stimulation, wind and ocean current directions, and biorhythms. Statistical methods for handling such data have developed rapidly in the last twenty years, particularly data display, correlation, regression and analysis of tempered or spatially structured data. Further, some of the exciting modern developments in general statistical methodology, particularly nonparametric smoothing methods and bootstrap-based methods, have contributed significantly to relatively intractable data analysis problems. This book provides a unified and up-to-date account of techniques for handling circular data.

By making both causal and process analyses possible, panel data has enjoyed increasing popularity in empirical science. In this compilation, several statistical techniques are presented in the face of

Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.

Panel data, which consist of information gathered from the same individuals or units at several different points in time, are commonly used in the social sciences to test theories of individual and s

This easy-to-understand introduction emphasizes the areas of probability theory and statistics that are important in environmental monitoring, data analysis, research, environmental field surveys, and

Presents techniques for making data from the social sciences accessible to nontechnical audiences. Discusses insights from visual perception research relating to graphing data, and explores graphs for

The process of analyzing qualitative data and producing a complete study is discussed in this book. Breaking down the transformation process into description, analysis and interpretation, Harry Wolcot

A summary of the techniques, tools, and concepts developed during the last 15 years that have been used to determine and estimate the relative risks of engineering designs, whether they result from de

This is the first comprehensive, yet clearly presented, account of statistical methods for analysing spherical data. The analysis of data, in the form of directions in space or of positions of points on a spherical surface, is required in many contexts in the earth sciences, astrophysics and other fields, yet the methodology required is disseminated throughout the literature. Statistical Analysis of Spherical Data aims to present a unified and up-to-date account of these methods for practical use. The emphasis is on applications rather than theory, with the statistical methods being illustrated throughout the book by data examples.

This book presents statistical methods for analysis of the duration of events. The primary focus is on models for single-spell data, events in which individual agents are observed for a single duration. Some attention is also given to multiple-spell data. The first part of the book covers model specification, including both structural and reduced form models and models with and without neglected heterogeneity. The book next deals with likelihood based inference about such models, with sections on full and semiparametric specification. A final section treats graphical and numerical methods of specification testing. This is the first published exposition of current econometric methods for the study of duration data.

The 1990 United States Census was the most exhaustive in history. The vast majority of census users seek information about local areas, yet they lack examples or methodology texts prepared by experts

Explicates the many analytical techniques and computer programs available to extract biological information from the radio tracking data. Presents software programs for solving specific problems, and

The Statistical Analysis of Discrete Data provides an up-to-date introduction to methods for analyzing discrete data. The text covers both single-sample problems and problems with structured means whi

Researchers often do not analyze nonreplicated experiments statistically because they are unfamiliar with existing statistical methods that may be applicable. Analysis of Messy Data, Volume II details

This monograph reviews some of the work that has been done for longitudi- nal data in the rapidly expanding field of nonparametric regression. The aim is to give the reader an impression of the basic

Random Signals, Noise and Filtering develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: (1) fundamen

Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to t

First half of book presents fundamental mathematical definitions, concepts, and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text and numerous worke

Survival analysis deals with the distribution of life times, essentially the times from an initiating event such as birth or the start of a job to some terminal event such as death or pension. This bo

Data Structures and Algorithm Analysis in Java is an advanced algorithms book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was k

Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis provides the mathematical background necessary for students preparing for a career as a statistician