A Convolution of two geometric distributions

AI Thread Summary
The discussion focuses on deriving the convolution of two geometric distributions, specifically addressing the summation process involved. The initial summation presented was incorrect, as it began at k=1 instead of k=2, which is necessary since the smallest value for the sum of two geometric random variables is 2. The correct formulation should be $$P(X+Y=z) = \sum_{k=2}^{z} (1-p)^{k-1}p^2(1-p)^{z-k-1}$$. Participants referenced external sources, including a Stack Exchange link, to clarify the proper approach and confirm the validity of the derived probabilities for specific values of z. The conversation emphasizes the importance of correctly defining the limits of summation in probability distributions.
Ad VanderVen
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I am trying to derive the convolution of two geometric distributions but obviously I am making an error.
I'm trying to derive the convolution from two geometric distributions, each of the form:
$$\displaystyle \left( 1-p \right) ^{k-1}p$$ as follows $$\displaystyle \sum _{k=1}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}.$$ with as a result: $$\displaystyle \left( 1-p \right) ^{z-2}{p}^{2}z$$ Now the sum: $$\displaystyle \sum _{z=2}^{\infty } \left( 1-p \right) ^{-2+z}{p}^{2}z.$$ should be equal to ##\displaystyle \frac{2}{p}## which is not the case.

What am I did wrong?
 
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$$\displaystyle \sum _{k=1}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}$$ seems strange. You sure it's not $$\displaystyle \sum _{k=1}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k+1}\ ? $$
 
Ad VanderVen said:
I'm trying to derive the convolution from two geometric distributions, each of the form:
$$\displaystyle \left( 1-p \right) ^{k-1}p$$
That indicates that you define the geometric distribution at ##k## to be the probability of success on the ##k##-th attempt, as oppose to the probability of success after ##k## failures.

So , as noted on the stackexchange link, if you consider the sum of two geometric random variables, the smallest possible value of ##k## is 2, which results when you succeed on the 1st try from the first distribution and again on the first try from the second distribution. So it isn't clear why you are writing a summation beginning with ##k = 1##.
as follows $$\displaystyle \sum _{k=1}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}.$$
 
Stephen Tashi said:
So , as noted on the stackexchange link, if you consider the sum of two geometric random variables, the smallest possible value of ##k## is 2, which results when you succeed on the 1st try from the first distribution and again on the first try from the second distribution. So it isn't clear why you are writing a summation beginning with ##k = 1##.
I'm afraid you're absolutely right. Only then will you get $$\displaystyle P \left( X+Y=z \right) \, = \,\sum _{k=2}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}$$
 
Ad VanderVen said:
The case is treated at: https://math.stackexchange.com/ques...of-two-independent-geometric-random-variables and the summation:$$\displaystyle \sum _{k=1}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}$$ must be$$\displaystyle \sum _{k=1}^{z-1} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}.$$

That formula comes from the message on stackexchange that asked the question and conjectured a formula. Look at the formulas given by the messages that answered the question.

Ad VanderVen said:
$$\displaystyle P \left( X+Y=z \right) \, = \,\sum _{k=2}^{z} \left( 1-p \right) ^{k-1}{p}^{2} \left( 1-p \right) ^{z-k-1}$$

##P(X+Y =2) = p^2##, Does the above formula agree with that when ##z = 2##?

##P(X+Y = 3) = p(1-p)p + (1-p)pp = 2(1-p)p^2 ##
 
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