# Functions for Pre-Processing Data for Multivariate Data Visualisation using Tours

## Documentation for package ‘mulgar’ version 1.0.2

- DESCRIPTION file.
- Package NEWS.

## Help Pages

aflw | AFLW player statistics
box | 3D plane in 5D
bushfires | Australian bushfires 2019-2020
c1 | Challenge data sets
c2 | Challenge data sets
c3 | Challenge data sets
c4 | Challenge data sets
c5 | Challenge data sets
c6 | Challenge data sets
c7 | Challenge data sets
calc_mv_dist | Compute Mahalanobis distances between all pairs of observations
calc_norm | Calculate the norm of a vector
clusters | Three clusters in 5D
clusters_nonlin | Four unusually shaped clusters in 4D
convert_proj_tibble | This function turns a projection sequence into a tibble
gen_vc_ellipse | Generate points on the surface of an ellipse
gen_xvar_ellipse | Ellipse matching data center and variance
ggmcbic | Produces an mclust summary plot with ggplot
ggscree | This function produces a simple scree plot
ggslice | Generate an axis-parallel slice display
ggslice_projection | Generate slice display
hierfly | Generate a dendrogram to be added to data
mc_ellipse | Computes the ellipses of an mclust model
multicluster | Multiple clusters of different sizes, shapes and distance from each other
norm_vec | Normalise a vector to have length 1
pca_model | Create wire frame of PCA model
pisa | PISA scores
plane | 2D plane in 5D
plane_nonlin | Non-linear relationship in 5D
pooled_vc | Compute pooled variance-covariance matrix
rmvn | Generate a sample from a multivariate normal
simple_clusters | Two clusters in 2D
sketches_test | Images of sketches for testing
sketches_train | Images of sketches for training
som_model | Process the output from SOM to display the map and data