Description Usage Arguments Details Value Examples

This function will plot the first few mafs in the dataset overlaid with a smooth version of the same maf and, if desired, confidence intervals. Additionally, an estimate of the number of mafs will be printed.

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`cexVal` |
The size of the labels in the plot |

`B` |
Number of replications in the confidence interval calculations |

`alpha` |
The significance level |

`block.size` |
The block size of the resampled residuals, i.e. the number of contiguous time steps to sample at the time from the set of residuals. |

`maf.object` |
The output of the |

`smoothSpan` |
Fraction between 0-1 that specifies the proportion of timesteps to include in the smoothing window, which is weighted by a tricubic. See ?loess for details. Alternatively, one can specify an integer greater than 1 which refers to the number of time points to include in the tricubic filter. |

`nmaf` |
The number of MAFs to plot |

`with.wncertainty` |
A logical specifying whether to plot the confidence interval around each maf. |

The confidence intervals are obtained using a resampling scheme which extracts the residuals of the original
time series after smoothing
with the same filter as the one parametrized by `smoothSpan`

. The residuals are
bootstrapped or block bootstrapped (if there is temporal structure in the residuals)
and added back to the smooth, creating a new data set. From the new data set a new set of
MAFs are calculated.

The smoothing parameter `smooth.span`

is also used when calculating the empirical
Signal-to-Noise ratio. Where we subtract the smooth from the time series and calculate
the variance of the smooth estimate over the residual variance. This gives an empirical
signal-to-noise estimate.

A plot of the MAFs and a list containing

`statStar`

Empirical SNR for each resampled MAF time series, i.e. a p x B matrix where p is the total number of predictors and B is the number of bootstraps/replications

`statObs`

The empirical SNR of the original MAF time series.

`pval`

The p-values of each MAF, where the p-value refers to the number of resampled MAFs that have a higher empirical SNR than the original MAFs. If there are less than

*α*, e.g. 0.05, resampled MAFs that have a higher empirical SNR than the original MAF, the MAF in question is not significant.

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