A random variable x has an F distribution if it can be written as a ratio
X=Y2/n2Y1/n1
between a Chi-square random variable Y1 with n1 degrees of freedom and a Chi-square random variable Y2, independent of Y1, with n2 degrees of freedom (where each of the two random variables has been divided by its degrees of freedom).
Definition Let X be a continuous random variable. Let its support be the set of positive real numbers:
RX=[0,∞)
Let n1, n2∈N . We say that X has an F distribution with n1 and n2 degrees of freedom if and only if its probability density function is
fX(x)=⎩⎨⎧cxn3/2−1(1+n2n1x)−(n1+n2)/20 if x∈RX if x∈RX
where c is a constant:
c=(n2n1)n1/2B(2n1,2n2)1
and B() is the Beta function.
Proof:
====E[X2]∫−∞∞x2fX(x)dx∫0∞x2cxn1/2−1(1+n2n1x)−(n1+n2)/2dxc∫0∞xn1/2+1(1+n2n1x)−(n1+n2)/2dxc∫0∞(n1n2t)n1/2+1(1+t)−(n1+n2)/2n1n2dt (by a change of variable: t=n2n1x)
=c(n1n2)n1/2+2∫0∞tn1/2+1(1+t)−n1/2−n2dt=c(n1n2)n1/2+2∫0∞t(n1/2+2)−1(1+t)−(n1/2+2)−(n2/2−2)dt=c(n1n2)n1/2+2B(2n1+2,2n2−2)(integral representation of Beta function)=(n2n1)n/2B(2n1,2n2)1(n1n2)n/2+2B(2n1+2,2n2−2)(substituting c )
=(n1n2)2B(2n1,2n2)1B(2n1+2,2n2−2)=(n1n2)2Γ(n1/2)Γ(n2/2)Γ(n1/2+n2/2)Γ(n1/2+2+n2/2−2)Γ(n1/2+2)Γ(n2/2−2)(definition of Beta function)=(n1n2)2Γ(n1/2)Γ(n2/2)Γ(n1/2+n2/2)Γ(n1/2+n2/2)Γ(n1/2+2)Γ(n2/2−2)
Finding a professional expert in "partial differential equations" in the advanced level is difficult.
You can find this expert in "Assignmentexpert.com" with confidence.
Exceptional experts! I appreciate your help. God bless you!
Comments