9783642320835 - Statistical Analysis of Climate Series: Analyzing, Plotting, Modeling, and Predicting with R de Pruscha, Helmut (10 resultados)

Condición: New. pp. 184.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book presents the application of statistical methods to climatological data on temperature and precipitation. It provides specific techniques for treating series of yearly, monthly and daily records. The results' potential relevance in the climate context is discussed.The methodical tools are taken from time series analysis, from periodogram and wavelet analysis, from correlation and principal component analysis, and from categorical data and event-time analysis.The applied models are - among others - the ARIMA and GARCH model, and inhomogeneous Poisson processes.Further, we deal with a number of special statistical topics, e.g. the problem of trend-, season- and autocorrelation-adjustment, and with simultaneous statistical inference.Programs in R and data sets on climate series, provided at the author's homepage, enable readers (statisticians, meteorologists, other natural scientists) to perform their own exercises and discover their own applications.

Hardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.

Condición: new. Questo è un articolo print on demand.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book presents the application of statistical methods to climatological data on temperature and precipitation. It provides specific techniques for treating series of yearly, monthly and daily records. The results' potential relevance in the climate context is discussed.The methodical tools are taken from time series analysis, from periodogram and wavelet analysis, from correlation and principal component analysis, and from categorical data and event-time analysis.The applied models are - among others - the ARIMA and GARCH model, and inhomogeneous Poisson processes.Further, we deal with a number of special statistical topics, e.g. the problem of trend-, season- and autocorrelation-adjustment, and with simultaneous statistical inference.Programs in R and data sets on climate series, provided at the author's homepage, enable readers (statisticians, meteorologists, other natural scientists) to perform their own exercises and discover their own applications. 184 pp. Englisch.

Condición: New. Print on Demand pp. 184 76 Illus.

Condición: New. PRINT ON DEMAND pp. 184.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book presents the application of statistical methods to climatological data on temperature and precipitation. It provides specific techniques for treating series of yearly, monthly and daily records. The results¿ potential relevance in the climate context is discussed.The methodical tools are taken from time series analysis, from periodogram and wavelet analysis, from correlation and principal component analysis, and from categorical data and event-time analysis.The applied models are - among others - the ARIMA and GARCH model, and inhomogeneous Poisson processes.Further, we deal with a number of special statistical topics, e.g. the problem of trend-, season- and autocorrelation-adjustment, and with simultaneous statistical inference.Programs in R and data sets on climate series, provided at the author¿s homepage, enable readers (statisticians, meteorologists, other natural scientists) to perform their own exercises and discover their own applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.

Buch. Condición: Neu. Statistical Analysis of Climate Series | Analyzing, Plotting, Modeling, and Predicting with R | Helmut Pruscha | Buch | viii | Englisch | 2012 | Springer | EAN 9783642320835 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.