Expected value of g(x)=1/(x+c) under gamma distribution

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PMRDK
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Homework Statement



Let [itex]g(x) = \frac{1}{x+c}[/itex], where [itex]c[/itex] is a positive constant, and [itex]x[/itex] is a random variable distributed according to the Gamma distribution
[itex]x\sim f(x)=\frac{1}{\Gamma(\alpha) \beta^\alpha} x^{\alpha \,-\, 1} e^{-\frac{x}{\beta}}[/itex].

I wish to calculate the expected value of [itex]g(x)[/itex] with respect to the probability density function [itex]f(x)[/itex].

Homework Equations



The expected value can be calculated as
[tex]E(g(x))=\int_0^∞g(x)f(x)dx = \int_0^∞ \frac{1}{x+c} \frac{1}{\Gamma(\alpha) \beta^\alpha} x^{\alpha \,-\, 1} e^{-\frac{x}{\beta}}dx[/tex]


The Attempt at a Solution


I have problems with calculating the integral. If [itex]g(x)=\frac{1}{x}[/itex], then the integral would not be too difficult. But the constant in the denominator gives me problems. I have attempted with variable substitutions and integration by parts. However, I have not been able to come up with a solution.
Actually, this is not a homework problem. I posted it here since it is `homework style', so I do not know if it is event possible to calculate the expectation.

Any help is much appreciated.
 
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The integral may not have a closed form. Do you know for sure if it does?

I'm not sure if this will help much, but you could try splitting up the integral into two, one from ##[0,c)## and the other on ##[c,\infty)##, and then expand the 1/(x+c) as a power series and integrate term by term to get a series expression. In the first integral, since x is smaller than c, you would use

$$\frac{1}{x+c} = \frac{1}{c} \frac{1}{1+x/c} = \frac{1}{c} \sum_{n=0}^\infty \left(\frac{x}{c}\right)^n,$$

while in the second term x is greater than c, so you would write

$$\frac{1}{x+c} = \frac{1}{x} \frac{1}{1+c/x} = \frac{1}{x} \sum_{n=0}^\infty \left(\frac{c}{x}\right)^n.$$

In principle one needs to be careful about switching the integral and the sum since the geometric series is only uniformly convergent on a domain ##|z-c| \leq R## for R < 1, so if you want to be rigorous I guess you could split up the integral into three regions, ##[0,c-\epsilon), [c-\epsilon,c+\epsilon], (c+\epsilon,\infty)## and do the series expansion for the first and the last, then estimate the error from neglecting the ##[c-\epsilon,c+\epsilon]## integral when taking ##\epsilon \rightarrow 0##, but my guess is that it won't cause problems.
 
PMRDK said:

Homework Statement



Let [itex]g(x) = \frac{1}{x+c}[/itex], where [itex]c[/itex] is a positive constant, and [itex]x[/itex] is a random variable distributed according to the Gamma distribution
[itex]x\sim f(x)=\frac{1}{\Gamma(\alpha) \beta^\alpha} x^{\alpha \,-\, 1} e^{-\frac{x}{\beta}}[/itex].

I wish to calculate the expected value of [itex]g(x)[/itex] with respect to the probability density function [itex]f(x)[/itex].

Homework Equations



The expected value can be calculated as
[tex]E(g(x))=\int_0^∞g(x)f(x)dx = \int_0^∞ \frac{1}{x+c} \frac{1}{\Gamma(\alpha) \beta^\alpha} x^{\alpha \,-\, 1} e^{-\frac{x}{\beta}}dx[/tex]


The Attempt at a Solution


I have problems with calculating the integral. If [itex]g(x)=\frac{1}{x}[/itex], then the integral would not be too difficult. But the constant in the denominator gives me problems. I have attempted with variable substitutions and integration by parts. However, I have not been able to come up with a solution.
Actually, this is not a homework problem. I posted it here since it is `homework style', so I do not know if it is event possible to calculate the expectation.

Any help is much appreciated.

Using b instead of 1/β, Maple evaluates this integral in terms of the incomplete Gamma function:

f:=b^a*x^(a-1)/GAMMA(a)*exp(-b*x);
f = b^a*x^(a-1)/GAMMA(a)*exp(-b*x)

J1:=int(f/(x+c),x=0..infinity) assuming a>0,b>0,c>0;
J1 = b^a*c^(a-1)*exp(c*b)*GAMMA(1-a,c*b)

That is,
[tex]\int_0^{\infty} \frac{b^a}{\Gamma(a)} \frac{x^{a-1}}{x+c} e^{-bx} \, dx<br /> = b^a c^{a-1} e^{bc} \Gamma(1-a,bc),[/tex]
where
[tex]\Gamma(u,z) = \int_z^{\infty} e^{-t} t^{u-1} \, dt \text{ if } z > 0[/tex]
is the incomplete Gamma function. I believe it has been proven that the incomplete Gamma function is non-elementary if u is not a positive integer.
 
Last edited:
Thank you for your help:smile:. So Maple was able to provide an answer in terms of a closed form solution (I tried in Maxima but did not succeed).
 
A more general problem has been solved here, for [itex]1/(1+cx^n)[/itex] and [itex]1/(1+cx)^n[/itex], for any [itex]n[/itex]:
http://www.pnas.org/content/107/51/22096.full.pdf+html?with-ds=yes

You can find there the explicit formula for the probability density function, the monotonicity properties of the pdf, the first and second moments for [itex]n=1[/itex] and [itex]n=2[/itex].