This is a detailed introduction to the statistical analysis of geophysical time series, using numerous examples and exercises to build proficiency. The exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra. The book also serves as a guide to using the open-source "R" program for statistical analysis of time series.
This is a detailed introduction to the statistical analysis of geophysical time series, using numerous examples and exercises to build proficiency. The exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra. The book also serves as a guide to using the open-source "R" program for statistical analysis of time series.
Taking a sequential approach to time-series model building, this easy-to-use and widely applicable book explores how to test for stationarity, normality, independence, linearity, model order, and...
Applications in Climatology and Atmospheric Sciences.- Subsampling Methodology for the Analysis of Nonlinear Atmospheric Time Series.- Global Patterns of Nonlinearity in Real and GCM-Simulated...
A new edition of the comprehensive, hands-on guide to financial time series, now featuring S-Plus® and R software Time Series: Applications to Finance with R and S-Plus®, Second Edition is designed...
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