Package: ltsa 1.4.6.1
ltsa: Linear Time Series Analysis
Methods of developing linear time series modelling. Methods are given for loglikelihood computation, forecasting and simulation.
Authors:
ltsa_1.4.6.1.tar.gz
ltsa_1.4.6.1.zip(r-4.7)ltsa_1.4.6.1.zip(r-4.6)ltsa_1.4.6.1.zip(r-4.5)
ltsa_1.4.6.1.tgz(r-4.6-x86_64)ltsa_1.4.6.1.tgz(r-4.6-arm64)ltsa_1.4.6.1.tgz(r-4.5-x86_64)ltsa_1.4.6.1.tgz(r-4.5-arm64)
ltsa_1.4.6.1.tar.gz(r-4.7-arm64)ltsa_1.4.6.1.tar.gz(r-4.7-x86_64)ltsa_1.4.6.1.tar.gz(r-4.6-arm64)ltsa_1.4.6.1.tar.gz(r-4.6-x86_64)
ltsa_1.4.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ltsa/json (API)
NEWS
| # Install 'ltsa' in R: |
| install.packages('ltsa', repos = c('https://angusian.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:74d44fea1c. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 100 | ||
| linux-devel-x86_64 | OK | 104 | ||
| source / vignettes | OK | 135 | ||
| linux-release-arm64 | OK | 128 | ||
| linux-release-x86_64 | OK | 109 | ||
| macos-release-arm64 | OK | 176 | ||
| macos-release-x86_64 | OK | 200 | ||
| macos-oldrel-arm64 | OK | 163 | ||
| macos-oldrel-x86_64 | OK | 342 | ||
| windows-devel | OK | 95 | ||
| windows-release | OK | 72 | ||
| windows-oldrel | OK | 86 | ||
| wasm-release | OK | 83 |
Exports:DHSimulateDLAcfToARDLLoglikelihoodDLResidualsDLSimulateexactLoglikelihoodinnovationVarianceis.toeplitzPredictionVarianceSimGLPtacvfARMAToeplitzInverseUpdateTrenchForecastTrenchInverseTrenchLoglikelihoodTrenchMean
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Linear Time Series Analysis | ltsa-package ltsa |
| Simulate General Linear Process | DHSimulate |
| Autocorrelations to AR parameters | DLAcfToAR |
| Durbin-Levinsion Loglikelihood | DLLoglikelihood |
| Prediction residuals | DLResiduals |
| Simulate linear time series | DLSimulate |
| Exact log-likelihood and MLE for variance | exactLoglikelihood |
| Nonparametric estimate of the innovation variance | innovationVariance |
| test if argument is a symmetric Toeplitz matrix | is.toeplitz |
| Prediction variance | PredictionVariance |
| Simulate GLP given innovations | SimGLP |
| theoretical autocovariance function (acvf) of ARMA | tacvfARMA |
| Inverse of Toeplitz matrix of order n+1 given inverse of order n | ToeplitzInverseUpdate |
| Minimum Mean Square Forecast | TrenchForecast |
| compute the matrix inverse of a positive-definite Toepliz matrix | TrenchInverse |
| Loglikelihood function of stationary time series using Trench algorithm | TrenchLoglikelihood |
| Exact MLE for mean given the autocorrelation function | TrenchMean |
