Guess the best normalization type from the stable interior of a distribution
Source:R/normalize-x.R
guess_normalize_type.RdApplies heuristics based on the support range, boundary mass, and zero
inflation to select among "asinh", "logit", and "rank_normal".
Proportions with boundary mass above boundary_mass_cutoff (at zero or
one) get "rank_normal"; "hurdle" is never auto-selected and must be
requested through vtype.
Usage
guess_normalize_type(
x,
range,
boundary_mass_cutoff = 0.1,
zero_tol = 1e-08,
one_tol = 1e-08
)Arguments
- x
Numeric vector of stable (non-sentinel, non-NA) winsorized values.
- range
Character range code used to clip the vector to its theoretical support before assessment.
- boundary_mass_cutoff
Proportion of values at or near zero (or one) that triggers the
"rank_normal"path. Default0.10.- zero_tol
Tolerance for identifying values near zero. Default
1e-8.- one_tol
Tolerance for identifying values near one. Default
1e-8.