Time Series A Biostatistical Introduction
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Time Series A Biostatistical Introduction
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Author : Peter Diggle
language : en
Publisher: Oxford University Press
Release Date : 2024-12-24
Time Series A Biostatistical Introduction written by Peter Diggle and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-24 with Mathematics categories.
Time series analysis is one of several branches of statistics whose practical importance has increased with the availability of powerful computational tools. Methodology that was originally developed for specialized applications, for example in finance or geophysics, is now widely available within general statistical packages. The second edition of Time Series: A Biostatistical Introduction is an introductory account of time series analysis, written from the perspective of applied statisticians whose interests lie primarily in the biomedical and health sciences. This edition has a stronger focus on substantive applications, in which each statistical analysis is directed at a specific research question. Separate chapters cover simple descriptive methods of analysis, including time-plots, smoothing, the correlogram and the periodogram; theory of stationary random processes; discrete-time models for single series; continuous-time models for single series; generalized linear models for time series of counts; models for replicated series; spectral analysis, and bivariate time series. The book is unique in its focus on biomedical and health science applications, which has been strengthened in this second edition. Nevertheless, the methods described are more widely applicable. It should be useful to teachers and students on masters-level degree courses in statistics, biostatistics and epidemiology, and to biomedical and health scientists with a knowledge of statistical methods at undergraduate level. Throughout, examples based on real datasets show a close interplay between statistical method and substantive science. This book will also describe the implementation of the methods in the R computing environment and provide access to R code and datasets.
Time Series
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Author : Peter Diggle
language : en
Publisher: Oxford University Press, USA
Release Date : 1990
Time Series written by Peter Diggle and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
Time-series analysis is one of several branches of statistics whose practical importance has increased with the availability of powerful computing tools. Methodology originally developed for specialized applications, for example in business forecasting or geophysical signal processing, is now widely available in general statistical packages. These computing developments have helped to bring the subject closer to the mainstream of applied statistics. This book is an introductory account of time-series analysis, written from the perspective of an applied statitician with a particular interest in biological applications. Throughout, analyses of data-sets drawn from the biological and medical sciences are integrated with the methodological development. The book is unique in its emphasis on biological and medical applications of time-series analysis. Nevertheless, its methodological content is more widely applicable. It should be useful to both students and practitioners of applied statistics whatever their field of application, and to biologists whose work involves the analysis of time-series data. Book jacket.
Time Series Analysis Univariate And Multivariate Methods
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Author : William W. S. Wei
language : en
Publisher: Pearson
Release Date : 2018-03-14
Time Series Analysis Univariate And Multivariate Methods written by William W. S. Wei and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-14 with Time-series analysis categories.
With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.
An Introduction To Time Series Analysis And Forecasting
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Author : Robert A. Yaffee
language : en
Publisher: Academic Press
Release Date : 2000-04-27
An Introduction To Time Series Analysis And Forecasting written by Robert A. Yaffee and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-04-27 with Mathematics categories.
A time series is a set of repeated measurements of the same phenomenon taken sequentially over time. Capturing the data creates a time series "memory" to document correlations or lack, and to help them make decisions based on this data.
Tutorials In Biostatistics Tutorials In Biostatistics
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Author : Ralph B. D'Agostino
language : en
Publisher: John Wiley & Sons
Release Date : 2004-11-30
Tutorials In Biostatistics Tutorials In Biostatistics written by Ralph B. D'Agostino and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11-30 with Mathematics categories.
The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the second of two volumes presenting the best tutorials published in SIM, focusing on statistical modeling of complex data. Topics include clustered data, hierarchical models, mixed models, genetic modeling, and meta-analysis. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.
Statistical Methods For Trend Detection And Analysis In The Environmental Sciences
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Author : Richard Chandler
language : en
Publisher: John Wiley & Sons
Release Date : 2011-03-25
Statistical Methods For Trend Detection And Analysis In The Environmental Sciences written by Richard Chandler and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-25 with Mathematics categories.
The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.
Statistical Analysis Of Geographical Data
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Author : Simon James Dadson
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-14
Statistical Analysis Of Geographical Data written by Simon James Dadson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-14 with Science categories.
Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.
Biostatistics For Medical And Biomedical Practitioners
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Author : Julien I. E. Hoffman
language : en
Publisher: Academic Press
Release Date : 2019-03-19
Biostatistics For Medical And Biomedical Practitioners written by Julien I. E. Hoffman and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-19 with Mathematics categories.
Basic Biostatistics for Medical and Biomedical Practitioners, Second Edition makes it easier to plan experiments, with an emphasis on sample size. It also shows what choices are available when simple tests are unsuitable and offers investigators an overview of how the kinds of complex tests that they won't do on their own work. The second edition presents a new, revised and enhanced version of the chapters, taking into consideration new developments and tools available, discussing topics, such as the basic aspects of statistics, continuous distributions, hypothesis testing, discrete distributions, probability in epidemiology and medical diagnosis, comparing means, regression and correlation. This book is a valuable source for students and researchers looking to expand or refresh their understanding of statistics as it applies to the biomedical and research fields. Based on the author's 40+ years of teaching statistics to medical fellows and biomedical researchers across a wide range of fields, it is a valuable source for researchers who need to understand more about biostatistics to apply it to their work. - Introduces procedures, such as multiple regression, Poisson distribution, binomial and multinomial distributions, variance analysis, and how to design and sample clinical trials - Presents a new section on ANCOVA - Gives references to free online tests - Includes over 200 diagrams, enabling the reader to visualize the results - Discusses NHST testing in detail, its disadvantages, and how to think about probability
Principles Of Multivariate Analysis
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Author : W. J. Krzanowski
language : en
Publisher: Oxford University Press
Release Date : 2000-09-28
Principles Of Multivariate Analysis written by W. J. Krzanowski and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-09-28 with Mathematics categories.
Multivariate analysis is necessary whenever more than one characteristic is observed on each individual under study. Applications arise in very many areas of study. This book provides a comprehensive introduction to available techniques for analysing date of this form, written in a style that should appeal to non-specialists as well as to statisticians. In particular, geometric intuition is emphasized in preference to algebraic manipulation wherever possible. The new edition includes a survey of the most recent developments in the subject.
Numerical Methods For Nonlinear Estimating Equations
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Author : Christopher G. Small
language : en
Publisher: OUP Oxford
Release Date : 2003-10-02
Numerical Methods For Nonlinear Estimating Equations written by Christopher G. Small and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-02 with Mathematics categories.
Nonlinearity arises in statistical inference in various ways, with varying degrees of severity, as an obstacle to statistical analysis. More entrenched forms of nonlinearity often require intensive numerical methods to construct estimators, and the use of root search algorithms, or one-step estimators, is a standard method of solution. This book provides a comprehensive study of nonlinear estimating equations and artificial likelihoods for statistical inference. It provides extensive coverage and comparison of hill climbing algorithms, which, when started at points of nonconcavity often have very poor convergence properties, and for additional flexibility proposes a number of modifications to the standard methods for solving these algorithms. The book also extends beyond simple root search algorithms to include a discussion of the testing of roots for consistency, and the modification of available estimating functions to provide greater stability in inference. A variety of examples from practical applications are included to illustrate the problems and possibilities thus making this text ideal for the research statistician and graduate student. This is the latest in the well-established and authoritative Oxford Statistical Science Series, which includes texts and monographs covering many topics of current research interest in pure and applied statistics. Each title has an original slant even if the material included is not specifically original. The authors are leading researchers and the topics covered will be of interest to all professional statisticians, whether they be in industry, government department or research institute. Other books in the series include 23. W.J.Krzanowski: Principles of multivariate analysis: a user's perspective updated edition 24. J.Durbin and S.J.Koopman: Time series analysis by State Space Models 25. Peter J. Diggle, Patrick Heagerty, Kung-Yee Liang, Scott L. Zeger: Analysis of Longitudinal Data 2/e 26. J.K. Lindsey: Nonlinear Models in Medical Statistics 27. Peter J. Green, Nils L. Hjort & Sylvia Richardson: Highly Structured Stochastic Systems 28. Margaret S. Pepe: The Statistical Evaluation of Medical Tests for Classification and Prediction