Package: tsBSS 1.0.0
Markus Matilainen
tsBSS: Blind Source Separation and Supervised Dimension Reduction for Time Series
Different estimators are provided to solve the blind source separation problem for multivariate time series with stochastic volatility and supervised dimension reduction problem for multivariate time series. Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace. The package is fully described in Nordhausen, Matilainen, Miettinen, Virta and Taskinen (2021) <doi:10.18637/jss.v098.i15>.
Authors:
tsBSS_1.0.0.tar.gz
tsBSS_1.0.0.tar.gz(r-4.5-noble)tsBSS_1.0.0.tar.gz(r-4.4-noble)
tsBSS_1.0.0.tgz(r-4.4-emscripten)tsBSS_1.0.0.tgz(r-4.3-emscripten)
tsBSS.pdf |tsBSS.html✨
tsBSS/json (API)
| # Install 'tsBSS' in R: |
| install.packages('tsBSS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- WeeklyReturnsData - Logarithmic Returns of Exchange Rates of 7 Currencies Against US Dollar
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:ef2963d774. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 07 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 07 2024 |
Exports:AMUSEasympAMUSEbootAMUSEladleFixNAgFOBIgJADEgSOBIlbtestPVCSOBIasympSOBIbootSOBIladletssdrvSOBI
Dependencies:backportsbitbit64bootbroombroom.helpersBSSprepcardsclicliprclueclustercolorspacecpp11crayoncurlDBIdplyrfansifarverforcatsforecastfracdiffgenericsGGallyggplot2ggstatsgluegtablehavenhmsICSICSNPICtestisobandJADEjsonlitelabelinglabelledlatticelifecyclelmtestmagrittrMASSMatrixmgcvminqamitoolsmunsellmvtnormnlmennetnumDerivpatchworkpillarpkgconfigplyrpngprettyunitsprogresspurrrquadprogquantmodR6RColorBrewerRcppRcppArmadilloRcppRollreadrrlangscalesstringistringrsurveysurvivaltibbletidyrtidyselecttimeDatetseriesTTRtzdburcautf8vctrsviridisLitevroomwithrxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Blind Source Separation and Supervised Dimension Reduction for Time Series | tsBSS-package |
| Second-order Separation Sub-White-Noise Asymptotic Testing with AMUSE | AMUSEasymp AMUSEasymp.default AMUSEasymp.ts AMUSEasymp.xts AMUSEasymp.zoo |
| Second-order Separation Sub-White-Noise Bootstrap Testing with AMUSE | AMUSEboot AMUSEboot.default AMUSEboot.ts AMUSEboot.xts AMUSEboot.zoo |
| Ladle Estimator to Estimate the Number of White Noise Components in SOS with AMUSE | AMUSEladle AMUSEladle.default AMUSEladle.ts AMUSEladle.xts AMUSEladle.zoo |
| Class: bssvol | bssvol plot.bssvol print.bssvol |
| The FixNA Method for Blind Source Separation | FixNA FixNA.default FixNA.ts FixNA.xts FixNA.zoo |
| Generalized FOBI | gFOBI gFOBI.default gFOBI.ts gFOBI.xts gFOBI.zoo |
| Generalized JADE | gJADE gJADE.default gJADE.ts gJADE.xts gJADE.zoo |
| Generalized SOBI | gSOBI gSOBI.default gSOBI.ts gSOBI.xts gSOBI.zoo |
| Modified Ljung-Box Test and Volatility Clustering Test for Time Series. | lbtest print.lbtest |
| A Modified Algorithm for Principal Volatility Component Estimator | PVC PVC.default PVC.ts PVC.xts PVC.zoo |
| Second-order Separation Sub-White-Noise Asymptotic Testing with SOBI | SOBIasymp SOBIasymp.default SOBIasymp.ts SOBIasymp.xts SOBIasymp.zoo |
| Second-order Separation Sub-White-Noise Bootstrap Testing with SOBI | SOBIboot SOBIboot.default SOBIboot.ts SOBIboot.xts SOBIboot.zoo |
| Ladle Estimator to Estimate the Number of White Noise Components in SOS with SOBI | SOBIladle SOBIladle.default SOBIladle.ts SOBIladle.xts SOBIladle.zoo |
| Summary of an Object of Class tssdr | coef.summary.tssdr components.summary.tssdr plot.summary.tssdr print.summary.tssdr summary.tssdr |
| Supervised Dimension Reduction for Multivariate Time Series | components.tssdr plot.tssdr print.tssdr tssdr tssdr.default tssdr.ts tssdr.xts tssdr.zoo |
| A Variant of SOBI for Blind Source Separation | vSOBI vSOBI.default vSOBI.ts vSOBI.xts vSOBI.zoo |
| Logarithmic Returns of Exchange Rates of 7 Currencies Against US Dollar | WeeklyReturnsData |