Description Usage Arguments Value Note Author(s) References See Also

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.

1 | ```
lc_noise(tt, sig, SNR, redpart, alpha = 1.5)
``` |

`tt` |
numeric vector: Observation times given. |

`sig` |
numeric vector of same length as |

`SNR` |
positive number: Defines the relation between signal and noise (see |

`redpart` |
numeric value in [0,1]: Proportion of the power law noise in noise components (see |

`alpha` |
numeric value: Power law index for the power law noise component (see |

`y` |
numeric vector: Observed values: signal + noise. |

`s` |
numeric vector: Measurement accuracies related to the white noise component. |

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

Anita M. Thieler and Jonathan Rathjens

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>

Applied in `tsgen`

(see there for an example), applies `TK95_uneq`

.

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