Applied Time Series Analysis (Statistics: A Series of Textbooks and Monographs)

Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow The First Book Dedicated to This Class of Longitudinal Models Although antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models.

By gathering results scattered throughout the literature, Antedependence Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing.

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Simultaneous Inference in Regression provides a thorough overview of the construction methods and applications of Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice.

• Applied Time Series Analysis.
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Please accept our apologies for any inconvenience this may cause. Exclusive web offer for individuals. Large Covariance and Autocovariance Matrices 1st Edition. Nonparametric Models for Longitudinal Data: With Implementation in R 1st Edition. Methods and Applications with R 1st Edition. Missing and Modified Data in Nonparametric Estimation: With R Examples 1st Edition.

Chapman & Hall/CRC Monographs on Statistics and Applied Probability

Antedependence Models for Longitudinal Data 1st Edition. Simultaneous Inference in Regression 1st Edition. Theory, Applications, and Open Problems 1st Edition. Large Covariance and Autocovariance Matrices 1st Edition Arup Bose, Monika Bhattacharjee July 03, Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models.

Wu, Xin Tian May 15, Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. Lawless May 04, Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods applicable to many types of life history data. Methods and Applications with R 1st Edition Bing Li May 01, Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of Probabilistic Foundations of Statistical Network Analysis 1st Edition Harry Crane April 19, Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis.

With R Examples 1st Edition Sam Efromovich March 12, This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. Nelder, Yudi Pawitan August 04, This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder.

Gail July 26, Absolute Risk: Simultaneous Inference in Regression 1st Edition Wei Liu June 13, Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. The country you have selected will result in the following: Product pricing will be adjusted to match the corresponding currency. The title will be removed from your cart because it is not available in this region.

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Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: Over the last 15 years, singular spectrum analysis SSA has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing.

However, despite the promise it holds for time series Wynn December 21, Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. Cox September 28, Multidimensional scaling covers a variety of statistical techniques in the area of multivariate data analysis. Geared toward dimensional reduction and graphical representation of data, it arose within the field of the behavioral sciences, but now holds techniques widely used in many disciplines.

Barndorff-Nielsen, Claudia Kluppelberg August 09, Complex stochastic systems comprises a vast area of research, from modelling specific applications to model fitting, estimation procedures, and computing issues. The exponential growth in computing power over the last two decades has revolutionized statistical analysis and led to rapid developments Please accept our apologies for any inconvenience this may cause. Exclusive web offer for individuals.

Components of Variance 1st Edition.

Topics in Modelling of Clustered Data 1st Edition. Subset Selection in Regression 2nd Edition. Modeling and Statistical Analysis 1st Edition. Statistics in the 21st Century 1st Edition.

Subjective Probability Models for Lifetimes 1st Edition. Empirical Likelihood 1st Edition. Analysis of Time Series Structure: Computational Commutative Algebra in Statistics 1st Edition.

CRC Press Online - Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

Multidimensional Scaling 2nd Edition. Complex Stochastic Systems 1st Edition. Components of Variance 1st Edition D. Solomon July 30, Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing.

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Ryan, Helena Geys May 29, Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Subset Selection in Regression 2nd Edition Alan Miller April 15, Originally published in , the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade.

Modeling and Statistical Analysis 1st Edition Vilijandas Bagdonavicius, Mikhail Nikulin November 28, The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. Statistics in the 21st Century 1st Edition Adrian E.

Wells July 09, Exactly what is the state of the art in statistics as we move forward into the 21st century? Subjective Probability Models for Lifetimes 1st Edition Fabio Spizzichino June 28, Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Empirical Likelihood 1st Edition Art B. Owen May 18, Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data.