# Plot results of a evaluate.pm analysis

### Description

Create a simple plot of a time series and the results of a `evaluate.pm`

analysis (including the periodogram and the fitted OUSS power spectrum).

### Usage

1 2 |

### Arguments

`name` |
Character. A short name for the time series to be used for the plots (e.g. 'long-term study' or 'hare population'). |

`times` |
Numeric vector. The time points of the time series used for the analysis. Set to |

`signal` |
Numeric vector. The time series values (signal) used for the analysis. Set to |

`report` |
The value returned by |

`plotFile` |
An optional path to a PDF file to be generated with the plot. |

`dataFile` |
An optional path to a data file for storing the time series and the results of the analysis. |

`sep` |
Separator to be used for the data file. Only relevant if |

### Author(s)

Stilianos Louca

### References

Louca, S., Doebeli, M. (2015) Detecting cyclicity in ecological time series, Ecology 96: 1724–1732

### See Also

`evaluate.pm`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
# generate cyclic time series by adding a periodic signal to an OUSS process
times = seq(0,20,0.25);
signal = 0.6 * cos(2*pi*times) + generate_ouss(times, mu=0, sigma=1, lambda=1, epsilon=0.5);
# find periodogram peak and estimate statistical significance
report = evaluate.pm( times=times,
signal=signal,
minPeakFreq=0.3,
minFitFreq=0.3,
startRadius=2);
# plot overview of periodogram peak analysis
plotReport(sprintf("Example"), times=times, signal=signal, report=report);
``` |

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.