Package: cts 1.0-26

Zhu Wang

cts: Continuous Time Autoregressive Models

Provides tools for fitting continuous-time autoregressive (CAR) and complex CAR (CZAR) models for irregularly sampled time series using an exact Gaussian state-space formulation and Kalman filtering/smoothing. Implements maximum-likelihood estimation with stable parameterizations of characteristic roots, model selection via AIC, residual and spectral diagnostics, forecasting and simulation, and extraction of fitted state estimates. Methods are described in Wang (2013) <doi:10.18637/jss.v053.i05>.

Authors:Granville Tunnicliffe-Wilson [aut], Zhu Wang [aut, cre], Cleve Moler [ctb, cph], Jack Dongarra [ctb, cph], Jim Bunch [ctb, cph], G. W. Stewart [ctb, cph], John Nash [ctb]

cts_1.0-26.tar.gz
cts_1.0-26.tar.gz(r-4.7-arm64)cts_1.0-26.tar.gz(r-4.7-x86_64)cts_1.0-26.tar.gz(r-4.6-arm64)cts_1.0-26.tar.gz(r-4.6-x86_64)
cts_1.0-26.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
cts/json (API)
NEWS

# Install 'cts' in R:
install.packages('cts', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • asth - Measurements of The Lung Function
  • V22174 - Measurments of Relative Aboundance

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

2.56 score 1 stars 24 scripts 767 downloads 11 exports 0 dependencies

Last updated from:0157c0fe16. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK99
linux-devel-x86_64OK101
source / vignettesOK138
linux-release-arm64OK104
linux-release-x86_64OK113
wasm-releaseOK98

Exports:carcar_controlfactabkalsmokalsmoCompplotSpecCarplotSpecLsspec.cispec.lsspectrumtsdiag

Dependencies: