Time Series Costationarity Determination
Undo autoreflection action for an EWS object (wd stationary)
Perform bootstrap stationarity test for time series
Produces plots from output of findstysol that attempt to group differe...
Convert wavelet coefficients for two time-varying functions into two f...
Computes localized autocovariance and searches for costationary soluti...
Perform running mean smoothing of an EWS object
Extractor function for csFSS object.
Given two time series find some time-varying linear combinations that ...
Form a particular linear combination of two time series and assess the...
Computes localized (wavelet) autocovariance function
Computes a Linear Combination Test Statistics
Plots solutions that are identified by findstysols
Compute the time-localized (unconditional) variance for a time series
Concatenate a set of solution results into one set
Plots results of a Bootstrap Test of Stationarity
Plot a csBiFunction object
Plot a csFSS object.
Produce plots from a csFSSgr object.
Plot localized autocovariance (lacv) object.
Compute p-value for parametric Monte Carlo test and optionally plot te...
Print a csBiFunction object.
Print acsFSS object.
Print csFSSgr object.
Print lacv class object
Combine two time series using a time-varying linear combination.
Summarize a csBiFunction object.
Summarize a csFSS object.
Summarize a csFSSgr object.
Summarizes a lacv object
A test statistic for stationarity
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>.