Chernoff's distribution

In probability theory, Chernoff's distribution, named after Herman Chernoff, is the probability distribution of the random variable

$Z={\underset {s\in \mathbf {R} }{\operatorname {argmax} }}\ (W(s)-s^{2}),$ where W is a "two-sided" Wiener process (or two-sided "Brownian motion") satisfying W(0) = 0. If

$V(a,c)={\underset {s\in \mathbf {R} }{\operatorname {argmax} }}\ (W(s)-c(s-a)^{2}),$ then V(0, c) has density

$f_{c}(t)={\frac {1}{2}}g_{c}(t)g_{c}(-t)$ where gc has Fourier transform given by

${\hat {g}}_{c}(s)={\frac {(2/c)^{1/3}}{\operatorname {Ai} (i(2c^{2})^{-1/3}s)}},\ \ \ s\in \mathbf {R}$ and where Ai is the Airy function. Thus fc is symmetric about 0 and the density ƒZ = ƒ1. Groeneboom (1989) shows that

$f_{Z}(z)\sim {\frac {1}{2}}{\frac {4^{4/3}|z|}{\operatorname {Ai} '({\tilde {a}}_{1})}}\exp \left(-{\frac {2}{3}}|z|^{3}+2^{1/3}{\tilde {a}}_{1}|z|\right){\text{ as }}z\rightarrow \infty$ where ${\tilde {a}}_{1}\approx -2.3381$ is the largest zero of the Airy function Ai and where $\operatorname {Ai} '({\tilde {a}}_{1})\approx 0.7022$ .