What is the distribution of difference of two Gamma Distributions ?

In summary: You are trying to integrate the function f(x,y) = \frac{ x^{\epsilon}exp(-x/\theta) y^k exp(-y/\theta)}{\theta^{1 + \epsilon} \Gamma(1+\epsilon) \theta^k \Gamma(k) } over the region in the first quadrant defined by X > Y.You first want to take the limit of the answer as \epsilon approaches zero.Thanks for your interest.
  • #1
ashish1789kgp
4
0
What is the distribution of the difference of two gamma distributions with same scale parameter, and shape parameter of the first one is k(1+e), e -> 0 and second one is k.

What i exactly want to know is the following.
X~Gamma(K(1+e),\theta)
Y~Gamma(K,\theta)
Prob (X>Y) or P(X-Y)>0.

While trying to integrate i am stuck at the following intermediate step.

int (0,inf) (y)^(Ke-1) exp(-y/"\theta") Gamma(K,y/"\thata") dy.

Please suggest any way out.
 
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  • #2
I don't know if I can solve the problem, but let me see if I can state it.

You want to integrate the function
[tex] f(x,y) = \frac{ x^{\epsilon}exp(-x/\theta) y^k exp(-y/\theta)}{\theta^{1 + \epsilon} \Gamma(1+\epsilon) \theta^k \Gamma(k) } [/tex]

over the region in the first quadrant defined by X > Y

Then you want to take the limit of the answer as [itex] \epsilon [/itex] approaches zero.
 
  • #3
Thanks for your interest.

In the function you have written, in place of \eps it is k*(1+\eps).
But this is the original function. I tried to solve it and went couple of rounds ahead, when i got stuck at the point i mentioned in my first post.
 
  • #4
So the problem is to find:

[tex] \lim_{\epsilon \rightarrow 0 } \int_0^\infty \int_y^\infty \frac{ x^{k(1+\epsilon)}exp(-x/\theta) y^k exp(-y/\theta)}{\theta^{k(1 + \epsilon)} \Gamma(k(1+\epsilon)) \theta^k \Gamma(k) } dx dy [/tex]
 
  • #5
for the integral dx, the limit is from 0 to y, instead of y to \inf [\tex]
 
  • #6
Why would the limit for dx be 0 to y ? Do we want to compute P(X > Y) or do we want to compute P(X < Y) ?

Intuitively, I would expect the answer to this problem to be 1/2.
 
  • #7
Yes, you are right. It will be from y to \inf.

We are interested to show that it is greater than 1/2 by a small constant factor that is a function of \epsilon and may be K and \theta.
 
  • #8
I don't understand how the integration that you asked about arises in solving the original problem.

int (0,inf) (y)^(Ke-1) exp(-y/"\theta") Gamma(K,y/"\thata") dy.

[tex] \int_0^\infty y^{ke-1} exp( - y/\theta) \Gamma(k, y/\theta) dy [/tex]

Have I interpreted the integral correctly?
 

1. What is a Gamma Distribution?

A Gamma Distribution is a continuous probability distribution that is used to model data with non-negative values. It is characterized by two parameters, shape (α) and rate (β), and is commonly used to model waiting times or the time between events.

2. What is the difference between two Gamma Distributions?

The difference between two Gamma Distributions is the result of subtracting the values of two Gamma random variables. In other words, it is the distribution of the difference between two events or waiting times modeled by Gamma Distributions.

3. How is the distribution of difference of two Gamma Distributions calculated?

The distribution of difference of two Gamma Distributions is calculated by taking the difference between the shape and rate parameters of the two distributions. This results in a new Gamma Distribution with a new set of parameters that describe the difference between the two original distributions.

4. What is the shape of the distribution of difference of two Gamma Distributions?

The shape of the distribution of difference of two Gamma Distributions is dependent on the shape parameters of the two original distributions. It can range from being symmetric to skewed, depending on the values of the shape and rate parameters.

5. How is the distribution of difference of two Gamma Distributions used in research or data analysis?

The distribution of difference of two Gamma Distributions is often used in hypothesis testing and statistical analysis to determine if there is a significant difference between two groups or events. It can also be used in modeling and forecasting data that follows a Gamma Distribution.

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