DeBoinR (version 1.0)

deboinr: Orders a data-set consisting of probability density functions on the same x-grid. Visualizes a boxplot of these functions based on the notion of distance determined by the user. Reports outliers based on the distance chosen and k value.

Description

Orders a data-set consisting of probability density functions on the same x-grid. Visualizes a boxplot of these functions based on the notion of distance determined by the user. Reports outliers based on the distance chosen and k value.

Usage

deboinr(
  x_grid,
  densities_matrix,
  distance = c("hellinger", "nLQD", "fisher_rao", "TV_dist", "CLR", "wasserstein",
    "BD_fboxplot", "MBD_fboxplot", "user_defined"),
  median_type = c("cross", "geometric"),
  center_PDFs = FALSE,
  user_dist = NULL,
  k = 1.5,
  num_cores = 1
)

Value

An deboinr object containing the following:

• density_order. Vector of indices corresponding to rows of densities_matrix that sort from closest to furthest from the median PDF.

• outliers. Vector of indices corresponding to rows of densities_matrix that are determined to be outliers.

• box_plot. ggplot object of graphic output by calling this method.

Arguments

x_grid

Vector. X values of the PDF

densities_matrix

Matrix. A n x p matrix where rows are individual PDFs and p matches the length of x_grid.

distance

Character. The distance metric to use for the pairwise distances, or one of the two band depth options.

median_type

Character. Whether the cross-median or the geometric median should be used.

center_PDFs

Logical. Whether or not the modes of all the PDFs should be aligned prior to performing any calculations.

user_dist

R Function. User-defined function that takes in two PDFs as vectors and returns a non-negative float corresponding to a distance between them.

k

Float. The factor by which to expand the IQR when calculating outliers.

num_cores

Integer. The number of cores to use if parallelizing the distance matrix calculations.

Examples

example_data = DeBoinR::pdf_data[1:100,]
xx = deboinr(DeBoinR::x_grid,
             as.matrix(example_data),
             distance = "hellinger",
             median_type = 'cross',
             center_PDFs = TRUE,
             num_cores = 1
)

print("about to print DeBoinR object...")
print(xx)