BGFA_cocoreg_interface
                        Apply GFA using the same interface as cocoreg()
BGFA_joint_info         Project BGFA components common to all datasets
                        back to the original space
PCA_cocoreg_interface   PCA projection using cocoreg interface
RGCCA_cocoreg_interface
                        COCOREG style analysis using RGCCA projection
SCA_cocoreg_interface   SCA projection using cocoreg interface
add_notches             Add notch-like gaussian snippets to an existing
                        signal x
apply_dc_meta           Apply extracted properties of a data collection
                        to a data collection (restore)
average_R2_dflst        Computes the R^2 (variance explained) between
                        two lists of data.frames
cocoreg                 The Common Components by Regression (CoCoReg)
                        algorithm
cocoreg_by_path         Compute D_joint for dataset i separately for
                        all paths Can be used to study path variability
compose                 Calculate the composition formed by applying
                        all functions in the given path to a dataset.
compose_all             Calculate the average of the composition formed
                        by applying all functions in all possible paths
                        to a dataset.
create_Z_linear         Contains functions to create synthetic datasets
                        with different properties. The
                        create_syn_data_*() functions follow the
                        scheme: "total variation = shared_by_all +
                        shared_by_subset + noise" Create signals
create_mappings         Generate all possible pairwise mappings between
                        the given multivariate datasets.
create_syn_data_puvar   A data collection with variables that "become
                        unrelated during measurement"
create_syn_data_toy     An illustrative synthetic data collection
create_syn_data_uds     A data collection with one unrelated dataset
create_syn_data_uvar    A collection with unrelated variables
create_syndata_mv       Create multivariate synthetic data
create_syndata_pwl      A non-linear data collection using piecewise
                        linearity
cshift                  Circularly shift vector elements
data_collections2ggdf   Catenate a set of data collections (lists of
                        data.frames) into a single molted data.frame.
data_matrix_rmse        Compute RMSE between data.matrices dm1 and dm2
dc_variability          Compute ds_variability for all datasets in a
                        data collection
df_ggplot_melt          Melt data.frame into ggplottable format
df_scale                Apply scale on a numeric data.frame
df_scale_ols            Scales variables in data.frame dfx using
                        ordinary least squares such
dflst2array             Catenate a list of data.frames to a matrix
                        along dim
dflst2df                Catenate a list of data.frames vertically to a
                        single data.frame
dflst2dfmelt            Combine a list of data.frames to a single
                        molten data.frame
dflst_add_ds            Add a data.frame (dataset) to a list of
                        data.frames (datasets)
dflst_dsnames2varnames
                        Append dataset names to variable names of the
                        respective dataset
dflst_pca               Apply PCA to the data after catenating
                        data.frames horizontally
dl_remove_NA            Remove rows with NA values from a list of
                        data.frames
dl_scale                Run scale() on a list of data.frames
ds_variability          Compute variability_components for a dataset
generate_mapping_function
                        Generate a mapping function between two
                        datasets
generate_paths          Generate all/some paths between points
generate_paths_cyclic   Generate cyclic paths
generate_paths_noncyclic
                        Generate non-cyclic paths
get_dc_meta             Extract important properties of data collection
get_range_datalist      Get [min, max] of a list of numeric objects
get_starting_dataset    Helper function to get the starting dataset
                        based on a path.
ggcompare_dclst         Compare data collections variable by variable
ggplot_dclst            Plotting data collections using ggplot
ggplot_df               Plotting data.frame using ggplot
ggplot_dflst            Plot a list of data.frames using ggplot2
make_data_gauss_2d      Make 2D gauss data (maybe obsolete)
mapping_glmnet          Define a mapping function using glmnet::glmnet
mapping_lm              Mapping stats::lm
mapping_lmridge         Define a mapping function using MASS::lm.ridge
mapping_pcr             Define a mapping function using pls::pcr
mapping_rf              Mapping randomForest
mapping_rlm             Mapping MASS::rlm
mapping_svm             Mapping svm
mapping_svm_sigmoid     Mapping svm using sigmoid
mappings_R2_matrix      Extract R2 values from a list of mappings using
                        summary()
matrix_variability      Compute "variance" of the matrices using
                        Frobenius norm. Variance is by default computed
                        with respect to the mean of the matrices.
nplst_reorder_grid      Reorders a nested list of ggplots
rename_variables        Rename variables of a data collection
repmat                  Replicate matrix to create a larger one
rmse                    Compute RMSE between vectors v1 and v2
rotation_matrix         A rotation matrix
row_suffle_variability
                        Determine the variability of matrices under row
                        shuffling
se                      Standard error of mean
ss                      Sum of squares
svm_sigmoid             SVM using sigmoid kernel
to_unit_vec             Make vector of unit norm
traverse_nested_list    Apply fun to the bottom level of a nested list
                        structure
validate_data           Validate a data collection for use with cocoreg
var_explained           Sum-of-squares values showing what portion of
                        variance in dvec is explained by dvec_est
variability_components
                        Compute total, within group and between group
                        variability using fun
variation_shared_by     Return a specific variation component
vecnorm                 Compute Euclidean norm of vector
vector_variability      Compute "variance" of the vectors var()
wrapper_BGFA            Run BGFA by Klami et. al. using data format
                        conventions of this repo
