print.csFSS {costat} | R Documentation |
csFSS
object.
Print information about a csFSS
object.
## S3 method for class 'csFSS' print(x, ...)
x |
The |
... |
Other arguments. |
None
Guy Nason
Cardinali, A. and Nason, Guy P. (2013) Costationarity of Locally Stationary Time Series Using costat. Journal of Statistical Software, 55, Issue 1.
Cardinali, A. and Nason, G.P. (2010) Costationarity of locally stationary time series. J. Time Series Econometrics, 2, Issue 2, Article 1.
findstysols
, plot.csFSS
,
summary.csFSS
# # Create dummy data # x1 <- rnorm(32) y1 <- rnorm(32) # # Find stationary combinations. Note: normally Nsims would be much bigger # ## Not run: ans <- findstysols(Nsims=100, tsx=x1, tsy=y1) # # Print this csFSS object # ## Not run: print(ans) #Class 'csFSS' : Stationary Solutions Object from costat: # ~~~~~ : List with 13 components with names # startpar endpar convergence minvar pvals tsx tsy tsxname tsyname filter.number # family spec.filter.number spec.family # # #summary(.): #---------- #Name of X time series: x1 #Name of Y time series: y1 #Length of input series: 32 #There are 100 sets of solutions #Each solution vector is based on 3 coefficients #Some solutions did not converge, check convergence component for more information. #Zero indicates successful convergence, other values mean different things and #you should consult the help page for `optim' to discover what they mean #For size level: 0.05 # 0 solutions appear NOT to be stationary # 97 solutions appear to be stationary #Range of p-values: ( 0.885 , 0.975 ) # #Wavelet filter for combinations: 1 DaubExPhase #Wavelet filter for spectrum: 1 DaubExPhase