fit_highd_model: Construct the 2-D model and lift into high-dimensions
Description
This function fits a high-dimensional model using hexagonal bins and provides options
to customize the modeling process, including the choice of bin centroids or bin means,
removal of low-density hexagons, and averaging of high-dimensional data.
A list containing a list of a tibble contains scaled first and second columns
of NLDR data, and numeric vectors representing the limits of the original NLDR data (nldr_obj),
a object that contains hexagonal binning information (hb_obj),
a tibble with high-dimensional model (model_highd) and a tibble containing
hexagonal bin centroids in 2-D (model_2d), and
a tibble that contains the edge information (trimesh_data).
Arguments
highd_data
A tibble that contains the high-dimensional data with a unique identifier.
nldr_data
A tibble that contains the embedding with a unique identifier.
b1
(default: 4) A numeric value representing the number of bins along the x axis.
q
(default: 0.1) A numeric value representing the buffer amount as proportion of data range.
benchmark_highdens
(default: 5) A numeric value using to filter high-density hexagons.