functionHmono: Create a monotonically increasing DP-CDF by creating a K-degree noisy tree
Description
This function creates a storage tree of degree K using gran and range,
adds independent noise to each node proportional to epsilon, and then searches
the tree to create a DP-CDF. It then enforces monotonicity on the resuling
dpCDF.
Usage
functionHmono(eps, cdfstep, data, range, gran, K = 2, ...)
Arguments
eps
Epsilon value for Differential privacy control
cdfstep
The step sized used in outputting the approximate CDF; the values output are [min, min + cdfstep], [min, min + 2 * cdfstep], etc.
data
A vector of the data (single variable to compute CDFs from)
range
A vector length 2 containing user-specified min and max to truncate the universe to
gran
The smallest unit of measurement in the data (one [year] for a list of ages)
K
This sets the degree of the underlying tree.
...
Optionally add additional parameters.
Value
A list with 2 vectors: one is the y coordinates of the DP-CDF, the other is the
abs values of the anlytically expected bounds for a similarly-constructed
non-monotonized DP-CDF, at 95 percent probability.