Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topic..
Chapman & Hall/CRC Handbooks of Modern Statistical Methods
Handbook of Statistical Methods and Analyses in Sports. Swartz, Tim B. This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport baseball, football, hockey, basketball, and soccer followed by a section on other sports and general statistical design and analysis issues that are common to all sports. This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area.
The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of early phase studies. The need to accelerate drug development in a rapidly evolving context of targeted therapies, immunotherapy, combination treatments and complex group structures has provided the stimulus to these advances. Typically, we deal with very small samples, sequential methods that need to be efficient, while, at the same time adhering to et..
Handbook of Quantile Regression. Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analys..
It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research.
Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level c.. Longitudinal Data Analysis.
Handbook of Spatial Statistics edited by GELFAND, A. E., DIGGLE, P. J., FUENTES, M. and GUTTORP, P.
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data.
Each of these sections begins with an i.. Handbook of Big Data. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice. Offering balanced coverage of methodology, theory, and applications, this handbook: ul li Describes modern, scalable approaches for analyzing increasingly large datasets li li Defines the underlying concepts of the..
Handbook of Discrete-Valued Time Series. Holan, Scott H.
Lund, Robert. Model a Wide Range of Count Time Series strong Handbook of Discrete-Valued Time Series strong presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed can be applied to other types of discrete-valued time series, such as binary-valued or categorical time series.
Explore a Balanced Treatment of Frequentist and Bayesian Perspectives Accessible to graduate-level students who have taken an elementary class in statistical time series analysis, the.. Handbook of Cluster Analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools. The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments.
After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approac.. Handbook of Spatial Epidemiology.
Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space-time variations in disease incidences. These analyses can provide important information that leads to better decision making in public health.
Chapman & Hall/CRC Handbooks of Modern Statistical Methods
The first part of the book addresses general issues related to epidemiology, GIS, environmental studies, clustering, and ecological analysis. The second part presents basic statistical methods used in spatial epidemiology, inc..
Handbook of Neuroimaging Data Analysis. This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data.
Handbook of Spatial Statistics - CRC Press Book
Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph. Handbook of Survival Analysis. Van Houwelingen, Hans C. Ibrahim, Joseph G. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches.
It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: ul li An introduction to various areas in survival.. Handbook of Missing Data Methodology. Missing data affect nearly every discipline by complicating the statistical analysis of collected data.
The book also contains a section on space—time work as well as a section on important topics that build upon earlier chapters. By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.
Handbook of Spatial Statistics. Alan E. Continuous Spatial Variation. Continuous Parameter Stochastic Process Theory. Classical Geostatistical Methods. LikelihoodBased Methods. Asymptotics for Spatial Processes. Hierarchical Modeling with Spatial Data. Nonparametric Methods.
Parametric Methods. Modeling Strategies. Multivariate and Marked Point Processes. SpatioTemporal Processes. Continuous Parameter SpatioTemporal Processes. LowRank Representations for Spatial Processes. Constructions for Nonstationary Spatial Processes. Monitoring Network Design. Discrete Spatial Variation.