Think you've got this backwards. The exponential probability distribution is a gamma probability distribution only when the first parameter, k is set to 1. Consistent with the link below, if random variable X is distributed gamma(k,theta), then for gamma(1, theta), the random variable is distributed exponentially.
The gamma function in the denominator is equal to 1 when k=1. The denominator will reduce to theta when k = 1. The first term will be X0 = 1.
using t to represent theta, we have
f(x,t) = 1/t*exp(-x/t)
or we can substitute L = 1/t, and write an equivalent function:
f(x;L) = L*exp(-L*x) for x > 0
See:
http://en.wikipedia.org/wiki/Gamma_distribution
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To the untrained eye the question might seem backwards after a quick Google search, yet qouting wikipedia lacks deeper insight in to the question: What the question is referring to is a class of functions that factor into the following form:
f(y;theta) = s(y)t(theta)exp[a(y)b(theta)] = exp[a(y)b(theta) + c(theta) + d(y)]
where a(y), d(y) are functions only reliant on y and where b(theta) and c(theta) are answers only reliant on theta, an unkown parameter.
if a(y) = y, the distribution is said to be in "canonical form" and b(theta) is often called the "natural parameter"
So taking the gamma density function, where alpha is a known shape parameter and the parameter of interest is beta, the scale parameter. The density function follows as:
f(y;beta) = {(beta^alpha)*[y^(alpha - 1)]*exp[-y*beta]}/gamma(alpha)
where gamma(alpha) is defined as (alpha - 1)!
Hence the gamma-density can be factored as follows:
f(y;beta) = {(beta^alpha)*[y^(alpha - 1)]*exp[-y*beta]}/gamma(alpha)
=exp[alpha*log(beta) + (alpha-1)*log(y) - y*beta - log[gamma(alpha)]
from the above expression, the canonical form follows if:
a(y) = y
b(theta) = -beta
c(theta) = alpha*log(beta)
d(y) = (alpha - 1)*log(y) - log[gamma(alpha)]
which is sufficient to prove that gamma distributions are part of the exponential family.
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To prove the hypothesis. To disprove the hypothesis.
does not prove
you dont silly :)
A strong positive correlation does not prove causation. People only get sunburned during daylight hours. Sundials only work during daylight hours. Therefore sundials cause sunburns. The above sentences show how absurd such predicate thinking could be. Simply because two events usually occur at the same time does not mean they are related. One man found a perfect correlation between the price of whiskey and Chicago school teachers' salaries. No possible relationship could possibly exist except the rate of prosperity and inflation. Causation is difficult to prove.
Yes.When my son was pooping and he came out there was white stuff (semen)