Algorithms for Linear Time Series Analysis: With R Package

نویسندگان

  • A. Ian McLeod
  • Hao Yu
  • Zinovi L. Krougly
چکیده

Our ltsa package implements the Durbin-Levinson and Trench algorithms and provides a general approach to the problems of fitting, forecasting and simulating linear time series models as well as fitting regression models with linear time series errors. For computational efficiency both algorithms are implemented in C and interfaced to R. Examples are given which illustrate the efficiency and accuracy of the algorithms. We provide a second package FGN which illustrates the use of the ltsa package with fractional Gaussian noise (FGN). It is hoped that the ltsa will provide a base for further time series software.

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تاریخ انتشار 2007