cts: An R package for continuous time autoregressive models via Kalman filter

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We describe an R package cts for fitting a modified form of continuous time autoregressive model, which can be particularly useful with unequally sampled time series. The estimation is based on the application of the Kalman filter. The paper provides the methods and algorithms implemented in the package, including parameter estimation, spectral analysis, forecasting, model checking and Kalman smoothing. The package contains R functions which interface underlying Fortran routines. The package is applied to geophysical and medical data for illustration.

Original languageEnglish (US)
Pages (from-to)1-19
Number of pages19
JournalJournal of Statistical Software
Volume53
Issue number5
DOIs
StatePublished - Apr 2013
Externally publishedYes

Keywords

  • Continuous time autoregressive model
  • Kalman filter
  • Kalman smoothing
  • R
  • State space model

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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