lc_noise: Noise and measurement accuracy generator for light curves

In RobPer: Robust Periodogram and Periodicity Detection Methods

Noise and measurement accuracy generator for light curves

Description

Generates measurement accuracies, a white noise component depending on them and a second (possibly power law, i.e. red) noise component which does not depend on the measurement accuracies. For more details see tsgen or Thieler, Fried and Rathjens (2016). See RobPer-package for more information about light curves.

Usage

lc_noise(tt, sig, SNR, redpart, alpha = 1.5)

Arguments

tt	numeric vector: Observation times given.
sig	numeric vector of same length as tt: A given signal to which the noise will be added.
SNR	positive number: Defines the relation between signal and noise (see tsgen for Details).
redpart	numeric value in [0,1]: Proportion of the power law noise in noise components (see tsgen for Details).
alpha	numeric value: Power law index for the power law noise component (see tsgen for Details).

Value

y	numeric vector: Observed values: signal + noise.
s	numeric vector: Measurement accuracies related to the white noise component.

Note

A former version of this function is used in Thieler et al. (2013).

Author(s)

Anita M. Thieler and Jonathan Rathjens

References

Thieler, A. M., Backes, M., Fried, R. and Rhode, W. (2013): Periodicity Detection in Irregularly Sampled Light Curves by Robust Regression and Outlier Detection. Statistical Analysis and Data Mining, 6 (1), 73-89

Thieler, A. M., Fried, R. and Rathjens, J. (2016): RobPer: An R Package to Calculate Periodograms for Light Curves Based on Robust Regression. Journal of Statistical Software, 69 (9), 1-36, <doi:10.18637/jss.v069.i09>

See Also

Applied in tsgen (see there for an example), applies TK95_uneq.

RobPer documentation built on June 13, 2022, 1:06 a.m.