choose_PCs.kurtosis |
Selects the principle components (PCs) of sufficient kurtosis from a SVD. |
choose_PCs.variance |
Selects the principle components of above-average variance from a SVD. |
clever |
Calculates PCA leverage or robust distance and identifies outliers. |
Dat1 |
Example fMRI Time Series for Subject 1 |
Dat2 |
Example fMRI Time Series for Subject 2 |
est_trend |
Estimates the trend of 'ts' using a robust discrete cosine transform. |
fit.F |
Estimates the parameters of the F distribution of MCD distances. |
id_out.leverage |
Identifies outliers based on leverage. |
id_out.robdist |
Identifies outliers based on robust distance. |
id_out.robdist_subset |
Identifies outliers based on robust distance, with adjustment for the subset method. |
leverage_images |
Calculate the leverage images for each outlier that meets the 'outlier_level' threshold, with 3 (default) being the highest/strictest and 1 being the lowest. |
logL.F |
Computes the log likelihood of a sample of values from an F distribution. |
logL.lnorm |
Computes the log likelihood of a sample of values from a log normal distribution. |
Matrix_to_VolumeTimeSeries |
Applies a 2D/3D mask to a matrix to get a 3D/4D volume time series. |
PC.leverage |
Computes PCA leverage. |
PC.robdist |
Computes MCD distances. |
PC.robdist_subset |
Computes MCD distances based on subsetting the data to reduce autocorrelation. |
PCATF |
PCA Trend Filtering. From: https://github.com/Lei-D/PCATF |
plot.clever |
Visualizes the outlier distribution of a clever object. |
scale_med |
Centers and scales a matrix robustly for the purpose of covariance estimation. |