Standard Normal CDF Infrastructure #
@cite{luce-1959}
Shared Gaussian CDF definitions and properties used by both Thurstone's discriminal-process theory (§2.D) and Signal Detection Theory (§2.E) in @cite{luce-1959}.
Definitions #
normalPDF: the standard normal density φ(t) = (1/√(2π)) exp(−t²/2)normalCDF: the standard normal CDF Φ(x) = ∫_{−∞}^{x} φ(t) dt
Properties #
Monotonicity, strict monotonicity, symmetry, boundary values, and bounds.
The CDF is defined via Mathlib's cdf (gaussianReal 0 1), which gives
normalCDF x = (gaussianReal 0 1).real (Iic x). This grounds the properties
in Mathlib's measure-theoretic Gaussian infrastructure.
The standard normal cumulative distribution function:
Φ(x) = ∫_{-∞}^{x} (1/√(2π)) exp(-t²/2) dt.
Defined as cdf (gaussianReal 0 1) x, the CDF of the standard Gaussian
measure evaluated at x.
Equations
Instances For
The normal CDF is non-negative: Φ(x) ≥ 0 for all x.
The normal CDF is at most 1: Φ(x) ≤ 1 for all x.
Φ(0) = 1/2 by symmetry of the standard normal distribution.
The normal CDF is strictly monotone increasing.
The normal CDF is injective (from strict monotonicity).