getpvals | R Documentation |
Given two time series, a set of combination coefficients, a function to combine them, this function makes the combination, tests the combination for stationarity, and returns the pvalue. Effectively, returns "how stationary" the combination is.
getpvals(par, prodcomb.fn, tsx, tsy, filter.number,
family=c("DaubExPhase", "DaubLeAsymm"),
verbose, tos = BootTOS, Bsims = 100, lapplyfn = lapply)
par |
The coefficients used to make the combination via the
|
prodcomb.fn |
The function which computes the combination given the two time series and the combination parameters. |
tsx |
One of the time series. |
tsy |
The other time series. |
filter.number |
Wavelet smoothness to be used in the time series combination. |
family |
Wavelet family to be used in the time series combination. |
verbose |
Supplied directly to the call to |
tos |
The function the computes a test of stationarity |
Bsims |
Number of bootstrap simulations the test uses (if it does) |
lapplyfn |
The function used to process lists. Can be the regular
|
A single number between zero and one indicating the p-value from the hypothesis test of stationarity of the combination.
G. P. 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
#
# Generate two toy time series data sets
#
x1 <- rnorm(32)
y1 <- rnorm(32)
#
# Generate two toy sets of parameters (for combination)
#
tmp.a <- c(1,-1)
tmp.b <- c(0.5, 0.5)
#
# Call the function and find out the degree of stationarity of this
# combination
#
## Not run: ans <- getpvals(c(tmp.a, tmp.b), prodcomb.fn=prodcomb, tsx=x1, tsy=y1,
filter.number=1, family="DaubExPhase")
## End(Not run)
#
# What is the p-value?
#
## Not run: ans
# [1] 0.53
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