About this product

Product Identifiers

PublisherOxford University Press, Incorporated

ISBN-100198522266

ISBN-139780198522263

eBay Product ID (ePID)52718

Product Key Features

Number of Pages268 Pages

Publication NameTime Series : a Biostatistical Introduction

LanguageEnglish

Publication Year1990

SubjectProbability & Statistics / General, Probability & Statistics / Time Series, Life Sciences / Biology

TypeTextbook

Subject AreaMathematics, Science

AuthorPeter J. Diggle

SeriesOxford Statistical Science Ser.

FormatUk-Trade Paper

Dimensions

Item Height0.6 in

Item Weight15.9 Oz

Item Length9.2 in

Item Width6.1 in

Additional Product Features

Intended AudienceCollege Audience

LCCN89-034018

Dewey Edition20

Reviews'Professor Diggle's writing is clear and to the point. This book is easy to read regardless of prior time series experience ... excellent addition to the time series literature in that it focuses on the analysis of real biomedical data.'Scott L. Zeger, School of Hygiene and Public Health, Johns Hopkins University, Statistics in Medicine 10:3, "The book emphasizes biological and medical applications, but will be particularly useful to students and practitioners of applied statistics in all fields of application, as well as to biologists whose work involves the analysis of time-series data."--The Bulletin of Mathematics Books, 'a welcome attempt to provide an introductory account with a strong biological and medical flavour ... This modestly priced and well-written paperback must be a strong competitor as an introductory text to time series analysis whether for class use or for private reading.'Paul Davies, University of Birmingham, Royal Statistical Society News and Notes, October 1991, 'The particular appeal of the book to readers of this journal will be the way in which real biological data sets are used to illuminate the theory.'Biometrics, December 1993, 'Professor Diggle's writing is clear and to the point. This book is easy to read regardless of prior time series experience ... excellent addition to the time series literature in that it focuses on the analysis of real biomedical data.'Scott L. Zeger, School of Hygiene and Public Health, Johns Hopkins University, Statistics in Medicine 10:3'a welcome attempt to provide an introductory account with a strong biological and medical flavour ... This modestly priced and well-written paperback must be a strong competitor as an introductory text to time series analysis whether for class use or for private reading.'Paul Davies, University of Birmingham, Royal Statistical Society News & Notes, October 1991'The particular appeal of the book to readers of this journal will be the way in which real biological data sets are used to illuminate the theory.'Biometrics, December 1993

Series Volume Number5

IllustratedYes

Dewey Decimal519.5/5

Table Of ContentIntroduction1. Simple descriptive methods of analysis2. Theory of stationery processes3. Spectral analysis4. Repeated measurements5. Fitting autoregressive moving average processes to data6. Forecasting7. Elements of bivariate time-series analysisReferencesAppendix A, B and C

SynopsisThis book is an introductory account of time-series analysis, examined from the perspective of an applied statistician specializing in biological applications. It includes covers exploratory methods, including time-plots, smoothing, the correlogram and periodgram, as well as the theory of stationary random processes, spectral analysis and regression modelling, repeated measurements, ARIMA modelling, forecasting, and bivariate time series analysis. The book emphasizes biological and medical applications, but will be particularly useful to students and practitioners of applied statistics in all fields of application, as well as to biologists whose work involves the analysis of time-series data., This book is an introductory account of time-series analysis, written from the perspective of an applied statistician with a particular interest in biological applications. Separate chapters cover exploratory methods, the theory of stationary random processes, spectral analysis, repeated measurements, ARIMA modelling, forecasting, and bivariate time-series analysis., 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 statistician with a particular interest in biological applications. Separate chapters cover exploratory methods, the theory of stationary random processes, spectral analysis, repeated measurements, ARIMA modelling, forecasting, and bivariate time-series analysis. 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, and it should be useful to both students and practitioners of applied statistics, whatever their specialization.

LC Classification NumberQA280.D54 1990