cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter

cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter

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 pac...

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Bibliographic Details
Main Author: Zhu Wang
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2013-04-01
Series:Journal of Statistical Software
Subjects:
continuous time autoregressive model
state space model
Kalman lter
Kalman smoothing
R
Online Access:http://www.jstatsoft.org/v53/i05/paper
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spelling doaj-e867374b90014d0f981bfc92b61a9e612020-11-24T22:49:20ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602013-04-01535cts : An R Package for Continuous Time Autoregressive Models via Kalman FilterZhu WangWe 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.http://www.jstatsoft.org/v53/i05/papercontinuous time autoregressive modelstate space modelKalman lterKalman smoothingR
collection DOAJ
language English
format Article
sources DOAJ
author Zhu Wang
spellingShingle Zhu Wang
cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
Journal of Statistical Software
continuous time autoregressive model
state space model
Kalman lter
Kalman smoothing
R
author_facet Zhu Wang
author_sort Zhu Wang
title cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
title_short cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
title_full cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
title_fullStr cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
title_full_unstemmed cts : An R Package for Continuous Time Autoregressive Models via Kalman Filter
title_sort cts : an r package for continuous time autoregressive models via kalman filter
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2013-04-01
description 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.
topic continuous time autoregressive model
state space model
Kalman lter
Kalman smoothing
R
url http://www.jstatsoft.org/v53/i05/paper
work_keys_str_mv AT zhuwang ctsanrpackageforcontinuoustimeautoregressivemodelsviakalmanfilter
_version_ 1725676280822628352

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