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.
- Continuous time autoregressive model
- Kalman filter
- Kalman smoothing
- State space model
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty