how to do integration ∫+∞−∞exp(−xn)dx, assuming n>1 ?
From wiki page Gaussian Integral: ∫+∞−∞exp(−x2)dx=√π
So, one can define a random variable X has
pdf(x)=1√πexp(−x2)
, since ∫+∞−∞pdf(x)dx=1. Actually, this is normal distribution.
Now, I'd like to define
pdf(x)=1cexp(−xn), but how much is c?
Or, ∫∞−∞exp(−xn)dx=?
There is a hint on wiki page Error Function:
Error function is erf(x)=2√π∫x0exp(−t2)dt, with erf(0)=0 and erf(+∞)=1.
So this means a pdf can be defined as pdf(x)=12erf(x).
Then, Generalized Error Function is defined as
En(x)=n!√π∫x0exp(−tn)dt
does this mean
∫+∞−∞exp(−xn)dx=2√πn!
?
Even so, there's still a problem: if n is not integer, how to calculate n!? Does it becomes Gamma function Γ(n)? like this:
∫+∞−∞exp(−xn)dx=2√πΓ(n)
Answer
n>1,t=xn:
∫∞0e−xndx=1n∫∞0t1n−1e−tdt=1nΓ(1n)=Γ(n+1n)
As for the integral over R: when n is even, double this, when n is odd, the integral does not converge.
No comments:
Post a Comment