Numerical correlation of random timeseries with different filtering (running mean)
PSP.CorAfterRollmean.Rd
Numerical correlation of random timeseries with different filtering (running mean)
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
Examples
temp <- replicate(1000,PSP.CorAfterRollmean(1000,1,0,0.5))
rowMeans(temp)
#> [1] 0.4991412 0.8204650 0.9296877
PSP.CorUntilF(c(0.5,0.5/10,0.5/50),1,0,1000,0.5)
#> [1] 0.5000000 0.8253528 0.9341159