Plot differentially private score histograms

This function computes and visualizes two-dimensional principal component score histograms, including the original scatter plot, the non-private empirical histogram, and one or more differentially private histogram estimates. It is a plotting wrapper around dp_score() and returns both the computed score output and ggplot objects.

Usage

dp_score_plot(
  X,
  eps,
  delta,
  bins,
  method = c("add", "sparse"),
  center = TRUE,
  standardize = FALSE,
  g_dppca = FALSE,
  cpp.option = FALSE,
  axes = c(1, 2)
)

Arguments

X

A numeric matrix or data frame. Rows correspond to observations and columns correspond to variables.

eps

Positive number defining the total epsilon privacy parameter.

delta

Number in (0, 1) defining the total delta privacy parameter.

bins

Integer vector of length 2 defining the number of histogram bins along the first and second score axes, respectively.

method

Character vector specifying which private histogram methods to compute. Use "add" for the additive Gaussian histogram and "sparse" for the sparse thresholded histogram. The default is c("add", "sparse").

center

A logical value indicating whether to center the columns of X before computing principal component directions. The default is TRUE.

standardize

A logical value indicating whether to scale the columns of X by their sample standard deviations after optional centering. The default is FALSE.

g_dppca

A logical value indicating whether to use private principal component directions. The default is FALSE. See dp_pc_dir() for details.

cpp.option

A logical value passed to dp_pc_dir() when g_dppca = TRUE. The default is FALSE.

axes

Integer vector of length 2 specifying the principal components used to construct the score coordinates. The default is c(1, 2).

Value

A list with components:

score

The output of dp_score().

plot

A list containing the scatter plot, histogram panels, and the combined patchwork plot.

See also

dp_score() for computing score histograms without plotting. dp_score_plot_group() for group-wise score histogram plots.

Examples

data(gau, package = "dppca")

# Use a small subset to keep the example fast.
X <- gau[1:300, ]

# Draw a private score plot using the additive histogram method.
set.seed(123)
score_plot <- dp_score_plot(
  X,
  eps = 3,
  delta = 1e-3,
  bins = c(8, 8),
  method = "add"
)
score_plot$plot$add


# Draw score plots for all available histogram methods.
set.seed(123)
score_plot <- dp_score_plot(
  X,
  eps = 3,
  delta = 1e-3,
  bins = c(8, 8)
)
score_plot$plot$all