EDIT: It turns out I just made a dumb mistake:
Simplify[Exp[x^2]*2^n*Pi*D[maxdist[n,x]/n*(1+Erf[x/Sqrt[2]])^(2-n),x]]
A portion of my "factor" is actually inside the derivative. Thanks to everyone who helped!
I'm using Mathematica to try to solve: https://math.stackexchange.com/questions/1700486
The probability distribution function (PDF) of the maximum of n standard normally distributed variables is:
(2^(1/2 - n)*n*(1 + Erf[x/Sqrt[2]])^(-1 + n))/(E^(x^2/2)*Sqrt[Pi]) To find the mode, I take the derivative and set equal to 0. The "raw" derivative is:
(2^(1 - n)*(-1 + n)*n*(1 + Erf[x/Sqrt[2]])^(-2 + n))/(E^x^2*Pi) - (2^(1/2 - n)*n*x*(1 + Erf[x/Sqrt[2]])^(-1 + n))/(E^(x^2/2)*Sqrt[Pi]) and Simplify will reduce it to:
-((n*(1 + Erf[x/Sqrt[2]])^(-2 + n)*(2 - 2*n + E^(x^2/2)*Sqrt[2*Pi]*x + E^(x^2/2)*Sqrt[2*Pi]*x*Erf[x/Sqrt[2]]))/(2^n*E^x^2*Pi)) Since I only need to see when this value is $0$, I can multiply it by anything that's not $0$ (or undefined), in particular:
Exp[x^2] 2^n Pi/n (1 + Erf[x/Sqrt[2]])^(2 - n) Multiplying the simplified derivative by that quantity yields:
2^n E^x^2 Pi (2^(1 - n)/(E^x^2 Pi) - (2^(1/2 - n) x (1 + Erf[x/Sqrt[2]])) / (E^(x^2/2) Sqrt[Pi])) Simplifying again, we have:
2 - E^(x^2/2) Sqrt[2 Pi] x - E^(x^2/2) Sqrt[2 Pi] x Erf[x/Sqrt[2]] The problem? This value no longer depends on $n$.
However, graphing the PDF for various values of $n$ shows that the mode changes:


