Generate power law (1/f) noise surrogates, following the algorithm of Timmer and Konig (1995).
pwrLaw(npts=1024,dt=1,mean=0,sdev=1,beta=2,fcut=0,nsim=1,genplot=T,verbose=T)
number of data points for 1/f surrogate time series
sampling interval
mean value for 1/f surrogate series
standard deviation for 1/f surrogate series
power law coefficient. Positive number will yield a negative slope.
frequency cutoff: below this frequency a plateau will be modeled. Set to zero (default) for no plateau.
Number of surrogate series to generate
generate summary plots (T or F)
verbose output (T or F)
These simulations use the random number generator of Matsumoto and Nishimura (1998). Power law noise series are generated following the algorithm of Timmer and Konig (1995).
M. Matsumoto, and T. Nishimura, (1998), Mersenne Twister: A 623-dimensionally equidistributed uniform pseudo-random number generator, ACM Transactions on Modeling and Computer Simulation, 8, 3-30.
J. Timmer and K. Konig (1995), On Generating Power Law Noise, Astronomy and Astrophysics: v. 300, p. 707-710.