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

In summary, the conversation discusses calculating a distribution function f(m,v) by taking partials of P(X<m, Y<v) with respect to m and v. The speaker is then confused about how to find the distribution function for P(X-Y > a) using f(m,v) and asks for resources or references. They are also unsure about whether to use partial derivatives with respect to Y and X to find the density or if there is another approach. The conversation ends with a proposed integral, but the speaker is unsure if it is the correct one.
  • #1
Rane3
2
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?
 
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  • #2
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.
 
  • #3
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?
 

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

1. What is a distribution function?

A distribution function is a mathematical function that describes the probability of a random variable taking on a specific value or falling within a certain range of values. It is used to model the behavior of random variables and is a fundamental concept in statistics and probability theory.

2. What does P(X-Y > a) represent?

P(X-Y > a) represents the probability that the difference between two random variables, X and Y, is greater than a. This is also known as the probability of a positive excess.

3. How is the distribution function used to compute P(X-Y > a)?

The distribution function is used to compute P(X-Y > a) by first finding the joint probability distribution of X and Y, and then integrating over the region where X-Y > a. This integration gives the probability of obtaining a positive excess greater than a.

4. What is the role of f(m,v) in computing P(X-Y > a)?

f(m,v) represents the probability density function of the joint distribution of X and Y. It is used to calculate the probability of different values of X and Y occurring together.

5. What factors can affect the value of P(X-Y > a) when computing with f(m,v)?

The value of P(X-Y > a) can be affected by the choice of probability density function f(m,v), the values of the parameters m and v, and the value of a. The specific distribution being modeled, such as normal or exponential, can also impact the probability calculation.

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