Distribution Function: Computing P(X-Y > a) w/ f(m,v)

Join the discussion
Ask a follow-up here, or get your own question answered by working scientists, mathematicians and engineers — people, not an autocomplete.
Real named experts · corrections over time · the nuance an AI answer skips
2 replies · 2K views
Rane3
Messages
2
Reaction score
0
I've computed a distribution function f(m,v) by taking partials of P(X<m, Y<v) with respect to m, v. Suppose I wanted the distribution function for P(X-Y > a). Since I know f(m,v), can I use that to help me compute my new distribution function by taking partials? If so, how? I'm a little confused about this. Any good resources/references?
 
Physics news on Phys.org
You mean you have a density function [tex]f(m,v)[/tex] - the (joint) distribution function
would be [tex]F(m,v) = P(X < m, Y < v)[/tex].

I'm not sure which of the following two items you want for your second question:

i) You want a specific calculation of [tex]P(X - Y > a)[/tex] for a given value of [tex]a[/tex]. In this case you calculate this double integral

[tex] \iint_{\{X-Y > a\}} f(x,y) \, dx dy[/tex]

ii) You want an expression for the distribution of the random variable [tex]Z = X - Y[/tex].
You can either work out it out as an integral:

[tex] P(Z \le z) = \iint_{\{X-Y \le z\}} f(x,y) \, dx dy[/tex]

or you can do a transformation of variables approach.
 
I am looking for the second description, although I just want the probability density. If I know that:
X>0
X-Y>Z
and I know f(x,y), how can I find the density for X-Y>Z by taking partial derivatives of the integral? I'm getting myself confused. Should it again be partials with respect to Y,X, like I used to find f(x,y) in the first place? It seems that when I setup my limits, there is no dependence on Y and that throws me off.
[tex]\int_{-\infty}^{X}\int_0^{X-z}f(x,y)dydx[/tex] Is this even the correct integral?