Recent content by Lewis7879

I'm actually suppose to do it like M(s,t)= yes I know that but will I get the solution of mgf of bivariate normal distribution ? I'm stuck current trying to derive it.

I'm actually suppose to do it like great idea it is possible to do it this way ? its a very long step. M(s,t)= e(xs+yt) ∫∫ fXY (x,y) dxdy = e(xs+yt) ∫∫ (1/(2π√(1-ρ2)σxσy)) exp [ [-1/2(1-ρ2)] [(x-μx/σx)2 + (y-μy/σy)2 - 2ρ(x-μx/σx)(y-μy/σy)}

Does anyone know the proof of joint moment generating functions for bivariate normal distributions? M_x,y (s,t)= E(e^(xs+yt))

Will I be able to find P(x+y≤1) after determine A?

Hello mathman there's a slight error with range I made in the question which is 0≤y≤x≤∞ There was no other problems with the question as I was asked this way.

I need help guys I can't understand this Can anyone explain thoroughly how do I form the range for this question? f(x,y)= e-x for 0≤x≤y≤∞ 0 Otherwise Find P(x+y≤1) I attempted this by integrating through the range of 0≤y≤(1-x) and 0≤x≤∞ but that...