PSP.CorAfterRollmean: Numerical correlation of random timeseries with different...
In EarthSystemDiagnostics/paleospec: Spectral tools for the ECUS group
View source: R/PSP.CorAfterRollmean.R
PSP.CorAfterRollmean R Documentation
Numerical correlation of random timeseries with different filtering (running mean)
Description
Numerical correlation of random timeseries with different filtering (running mean)
Usage
PSP.CorAfterRollmean(N, betaSignal, betaNoise, R)
Arguments
N
Number of points of the timeseries
betaSignal
powerlaw slope of the signal
betaNoise
powerlaw slope of the noise
R
expected correlation of the whole timeseries
Value
correlation of unfiltered, 10point mean and 50 point mean
Author(s)
Thomas Laepple
Examples
temp <- replicate(1000,PSP.CorAfterRollmean(1000,1,0,0.5))
rowMeans(temp)
PSP.CorUntilF(c(0.5,0.5/10,0.5/50),1,0,1000,0.5)
EarthSystemDiagnostics/paleospec documentation built on Feb. 17, 2024, 4:36 p.m.
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View source: R/PSP.CorAfterRollmean.R
| PSP.CorAfterRollmean | R Documentation |
Numerical correlation of random timeseries with different filtering (running mean)
Description
Numerical correlation of random timeseries with different filtering (running mean)
Usage
PSP.CorAfterRollmean(N, betaSignal, betaNoise, R)
Arguments
N |
Number of points of the timeseries |
betaSignal |
powerlaw slope of the signal |
betaNoise |
powerlaw slope of the noise |
R |
expected correlation of the whole timeseries |
Value
correlation of unfiltered, 10point mean and 50 point mean
Author(s)
Thomas Laepple
Examples
temp <- replicate(1000,PSP.CorAfterRollmean(1000,1,0,0.5))
rowMeans(temp)
PSP.CorUntilF(c(0.5,0.5/10,0.5/50),1,0,1000,0.5)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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