Spatial Data Analysis

The book aims to investigate methods and techniques for spatial statistical analysis suitable to model spatial information in support of decision systems. Over the last few years there has been a cons

This book is the provisional result of more than 10 years of continued discussion with friends and colleagues from neighbouring disciplines. Although only a small minority ofthe millions of GIS users

The National Institute of Justice (NIJ) is the research, development and evaluationagency of the US Department of Justice. The NIJ is dedicated to improvingknowledge and understanding of crime and jus

The Global Financial Crisis and the Eurozone crisis that has followed have drawn attention to weaknesses in financial records, information and data. These weaknesses have led to operational risks in f

The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also informatio

Ideology and Spatial Voting in American Elections addresses two core issues related to the foundations of democratic governance: how the political views of Americans are structured and how citizens' voting decisions relate to their ideological proximity to the candidates. Focusing on testing the assumptions and implications of spatial voting, this book connects the theory with empirical analysis of voter preferences and behavior, showing Americans cast their ballots largely in accordance with spatial voting theory. Stephen A. Jessee's research shows voters possess meaningful ideologies that structure their policy beliefs, moderated by partisanship and differing levels of political information. Jessee finds that while voters with lower levels of political information are more influenced by partisanship, independents and better informed partisans are able to form reasonably accurate perceptions of candidates' ideologies. His findings should reaffirm citizens' faith in the broad functioni

Ideology and Spatial Voting in American Elections addresses two core issues related to the foundations of democratic governance: how the political views of Americans are structured and how citizens' voting decisions relate to their ideological proximity to the candidates. Focusing on testing the assumptions and implications of spatial voting, this book connects the theory with empirical analysis of voter preferences and behavior, showing Americans cast their ballots largely in accordance with spatial voting theory. Stephen A. Jessee's research shows voters possess meaningful ideologies that structure their policy beliefs, moderated by partisanship and differing levels of political information. Jessee finds that while voters with lower levels of political information are more influenced by partisanship, independents and better informed partisans are able to form reasonably accurate perceptions of candidates' ideologies. His findings should reaffirm citizens' faith in the broad functioni

The first part of this title contained all statistical tests relevant to starting clinical investigations, and included tests for continuous and binary data, power, sample size, multiple testing, vari

Advances in Geo-Spatial Information Science presents recent advances regarding fundamental issues of geo-spatial information science (space and time, spatial analysis, uncertainty modeling and geo-vis

Missing data have long plagued those conducting applied research in the social, behavioral, and health sciences. Good missing data analysis solutions are available, but practical information about im

Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and

In this sequel to two earlier volumes, the authors now focus on the long-time behavior of evolution inclusions, based on the theory of extremal solutions to differential-operator problems. This approa

This book is the definitive guide to cash flow statement analysis and forecasting. It takes the reader from an introduction about how cash flows move within a business, through to a detailed rev

Now available in paperback Pro Oracle Spatial for Oracle Database 11g shows how to take advantage of Oracle Databases builtin feature set for working with locationbased data. A great deal of the infor

With continuous advancements and an increase in user popularity, data mining technologies serve as an invaluable resource for researchers across a wide range of disciplines in the humanities and socia

With continuous advancements and an increase in user popularity, data mining technologies serve as an invaluable resource for researchers across a wide range of disciplines in the humanities and socia

DATA ANALYSIS WITH MICROSOFT ACCESS 2010 is an introduction to Access with an emphasis on topics relevant to data analysis. The goal is to help the analyst gain a true understanding of data and the in

This most up-to-date, one-stop reference combines coverage of both theory and observational techniques, with introductory sections to bring all readers up to the same level. Written by outstanding re

This book describes methods and software implementations for the analysis of interval-censored data. The authors present the theoretical background for all methods and apply the methods to real data s

This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose th

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16.As with previous editions,

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16.As with previous editions,

This concise, self-contained and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.

Introduction to Proteomics gives a concise and coherent overview of every aspect of current proteomics technology. The book provides students with sufficient theoretical background to be able to plan,

Introduction to Proteomics gives a concise and coherent overview of every aspect of current proteomics technology. The book provides students with sufficient theoretical background to be able to plan,

Robot and Multibody Dynamics: Analysis and Algorithms provides a comprehensive and detailed exposition of a new mathematical approach, referred to as the Spatial Operator Algebra (SOA), for studying t

For experiments, dimensional analysis enables the design, checks the validity, orders the procedure and synthesises the data. Additionally it can provide relationships between variables where standard

Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidem

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, grap

Spatial information is pervaded by uncertainty. Indeed, geographical data is often obtained by an imperfect interpretation of remote sensing images, while people attach ill-defined or ambiguous labe

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to sele

General relativity provides our best description of gravitation in modern physics - currently all observations and tests of gravitational theories have agreed with it. GR is applied in fields as diverse as fundamental astronomy, astrophysics, geodesy, physics, and space sciences, where high-accuracy observations and measurements are taken or modeled. IAU Symposium 261 summarizes the present state of applied relativity. It considers the applications of general relativity in a wide range of disciplines: geodesy, navigation, solar system ephemerides, space missions, pulsar timing, high-accuracy astrometry, gravity waves, gravitational lenses, and black hole astrophysics. The future tests of general relativity based on improved observational accuracies and higher order developments of the theory are discussed in general. Specific projects designed to test the theory in the near future are also covered. This volume is a useful resource for all those interested in general and special relativ

Writing with healthcare researchers in mind, Patricia Cerrito (mathematics, U. of Louisville) and John Cerrito, a retail and consulting pharmacist, describe how the investigation of healthcare databas

Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, resea

Survival analysis is a class of statistical methods for studying the occurrence and timing of events. Statistical analysis of longitudinal data, particularly censored data, lies at the heart of social

Using Gerasa and Dura Europos as case studies this book analyses changes in spatial patterns in the Late Antique polis. It seeks to determine how much spatial change should be linked to religious chan

A pragmatic guide to performing meaningful qualitative analysisThis text helps students and social service personnel better evaluate agency programs using the various qualitative documents (such as c

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative

R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider

This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data ana