Calculate Leverage of Component Models


[Up] [Top]

Documentation for package ‘clever’ version 0.1.5

Help Pages

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.