Numerical correlation of random timeseries with different filtering (running mean)

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

Thomas Laepple

Examples

temp <- replicate(1000,PSP.CorAfterRollmean(1000,1,0,0.5))
rowMeans(temp)
#> [1] 0.4991726 0.8205169 0.9298821
PSP.CorUntilF(c(0.5,0.5/10,0.5/50),1,0,1000,0.5)
#> [1] 0.5000000 0.8253528 0.9341159