Package: costat 2.4.1

Guy Nason

costat: Time Series Costationarity Determination

Contains functions that can determine whether a time series is second-order stationary or not (and hence evidence for locally stationarity). Given two non-stationary series (i.e. locally stationary series) this package can then discover time-varying linear combinations that are second-order stationary. Cardinali, A. and Nason, G.P. (2013) <doi:10.18637/jss.v055.i01>.

Authors:Guy Nason [aut, cre], Alessandro Cardinali [aut, ctb]

costat_2.4.1.tar.gz
costat_2.4.1.tar.gz(r-4.5-noble)costat_2.4.1.tar.gz(r-4.4-noble)
costat_2.4.1.tgz(r-4.4-emscripten)costat_2.4.1.tgz(r-4.3-emscripten)
costat.pdf |costat.html✨
costat/json (API)

# Install 'costat' in R:
install.packages('costat', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • SP500FTSElr - Log-returns time series of the SP500 and FTSE100 indices
  • fret - Particular section of FTSE log-return series.
  • sret - Particular section of SP500 log-returns series.

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

1.52 score 33 scripts 310 downloads 29 exports 2 dependencies

Last updated 1 years agofrom:3338ff2e17. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-linuxOKNov 09 2024

Exports:AntiARBootTOSCOEFbothscalecoeftofnEWSsmoothRMextractCSfindstysolsgetpvalslacvLCTSLCTSreslocalvarmergexyplot.BootTOSplot.csBiFunctionplot.csFSSplot.csFSSgrplot.lacvplotBSprint.csBiFunctionprint.csFSSprint.csFSSgrprint.lacvprodcombsummary.csBiFunctionsummary.csFSSsummary.csFSSgrsummary.lacvTOSts

Dependencies:MASSwavethresh

Readme and manuals

Help Manual

Help pageTopics
Computes localized autocovariance and searches for costationary solutions to bivariate time series.costat-package costat
Undo autoreflection action for an EWS object (wd stationary)AntiAR
Perform bootstrap stationarity test for time seriesBootTOS
Produces plots from output of findstysol that attempt to group different solutions.COEFbothscale
Convert wavelet coefficients for two time-varying functions into two functions with respect to time.coeftofn
Perform running mean smoothing of an EWS objectEWSsmoothRM
Extractor function for 'csFSS' object.extractCS
Given two time series find some time-varying linear combinations that are stationary.findstysols
Particular section of FTSE log-return series.fret
Form a particular linear combination of two time series and assess the combination's stationarity p-valuegetpvals
Computes localized (wavelet) autocovariance functionlacv
Computes a Linear Combination Test StatisticsLCTS
Plots solutions that are identified by findstysolsLCTSres
Compute the time-localized (unconditional) variance for a time serieslocalvar
Concatenate a set of solution results into one setmergexy
Plots results of a Bootstrap Test of Stationarityplot.BootTOS
Plot a 'csBiFunction' objectplot.csBiFunction
Plot a 'csFSS' object.plot.csFSS
Produce plots from a 'csFSSgr' object.plot.csFSSgr
Plot localized autocovariance (lacv) object.plot.lacv
Compute p-value for parametric Monte Carlo test and optionally plot test statistic valuesplotBS
Print a 'csBiFunction' object.print.csBiFunction
Print a'csFSS' object.print.csFSS
Print 'csFSSgr' object.print.csFSSgr
Print lacv class objectprint.lacv
Combine two time series using a time-varying linear combination.prodcomb
Log-returns time series of the SP500 and FTSE100 indicesSP500FTSElr
Particular section of SP500 log-returns series.sret
Summarize a 'csBiFunction' object.summary.csBiFunction
Summarize a 'csFSS' object.summary.csFSS
Summarize a 'csFSSgr' object.summary.csFSSgr
Summarizes a lacv objectsummary.lacv
A test statistic for stationarityTOSts