Adding two distributions with same moment generating function

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Adding two distributions with the same moment generating function (mgf) does not yield a straightforward result. If the mgf of both distributions is Mx(t) = My(t) = (1/3 + 2/3e^t), the mgf of the sum of two independent random variables X and Y is (1/3 + 2/3e^t)^2. However, if considering the sum of the distributions themselves, it results in 2*(1/3 + 2/3e^t), which lacks practical significance. The distinction between adding mgfs and adding random variables is crucial for accurate interpretation. Understanding these differences is essential for proper application in probability theory.
trojansc82
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Homework Statement



I wanted to know what the result would be if you added two distributions with the same moment generating function.

For example, what would the result be of:

Mx(t) + My(t) if Mx(t) = (1/3 + 2/3et) and My(t) = (1/3 + 2/3et)

Homework Equations





The Attempt at a Solution



Would the solution be (1/3 + 2/3et)2?
 
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trojansc82 said:

Homework Statement



I wanted to know what the result would be if you added two distributions with the same moment generating function.

For example, what would the result be of:

Mx(t) + My(t) if Mx(t) = (1/3 + 2/3et) and My(t) = (1/3 + 2/3et)

Homework Equations




The Attempt at a Solution



Would the solution be (1/3 + 2/3et)2?

No. Denoting the mgf of X by M_X(t) we have the relationship
M_{a+bX}(t) = E(e^{t(a+bX)}) = E(e^{at}e^{btX})=e^{at}E(e^{btX})<br /> =e^{at}M_X(bt)

You are asking about the mgf of X + X = 2X. So using the above with a = 0 and b = 2 gives M_{2X}(t) = M_X(2t).
 
trojansc82 said:

Homework Statement



I wanted to know what the result would be if you added two distributions with the same moment generating function.

For example, what would the result be of:

Mx(t) + My(t) if Mx(t) = (1/3 + 2/3et) and My(t) = (1/3 + 2/3et)

Homework Equations





The Attempt at a Solution



Would the solution be (1/3 + 2/3et)2?

There is a difference between adding distributions (or mgf's) and adding random variables. Which do you mean? If you want to find the MGF of X+Y, and assuming X,Y are independent, you get (1/3 + 2/3*exp(t))^2. If you want to find the MGF of the sum of the distributions of X and Y, you get 2*(1/3 + 2/3*exp(t)), but this thing does not really have much meaning.

RGV
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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