Robust Periodogram and Periodicity Detection Methods
Robust fit of a Beta distribution using CvM distance minimization
Disturbing light curve data
S-Regression using the Fast-S-Algorithm
Tau-Regression using the Fast-tau-Algorithm
Noise and measurement accuracy generator for light curves
The RobPer-package
Periodogram based on (robustly) fitting a periodic function to a light...
Generator for irregularly sampled observation times
Generator for periodic signal in a light curve
Power law noise generator
Power law noise generator for unequally sampled observation times
Artificial light curve generator
Designmatrix generator
Calculates periodograms based on (robustly) fitting periodic functions to light curves (irregularly observed time series, possibly with measurement accuracies, occurring in astroparticle physics). Three main functions are included: RobPer() calculates the periodogram. Outlying periodogram bars (indicating a period) can be detected with betaCvMfit(). Artificial light curves can be generated using the function tsgen(). For more details see the corresponding article: Thieler, Fried and Rathjens (2016), Journal of Statistical Software 69(9), 1-36, <doi:10.18637/jss.v069.i09>.