Joint Moment Generating Function Help

AI Thread Summary
The discussion revolves around the joint moment generating function MXY(s,t) = 1/(1-2s-3t+6st) for random variables X and Y, with constraints s<1/2 and t<1/3. Participants are trying to find probabilities P(min(X,Y) > 0.95) and P(max(X,Y) > 0.8). There is also a query about representing MXY(s,t) in the product form M1(s) · M2(t). One participant suggests a potential representation as 1/(1-2s) · 1/(1-3t), prompting further discussion. The thread highlights the challenges in deriving the required probabilities and the correct representation of the joint moment generating function.
wannabe92
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Hi, I've no idea where to go with the question below:

Joint moment generating function of X and Y - MXY(s,t) = 1/(1-2s-3t+6st)
for s<1/2, t<1/3.

Find P(min(X,Y) > 0.95) and P(max(X,Y) > 0.8)
 
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wannabe92 said:
Hi, I've no idea where to go with the question below:

Joint moment generating function of X and Y - MXY(s,t) = 1/(1-2s-3t+6st)
for s<1/2, t<1/3.

Find P(min(X,Y) > 0.95) and P(max(X,Y) > 0.8)

Can you represent M_{XY}(s,t) in the form M_1(s) \cdot M_2(t)?

RGV
 
Ray Vickson said:
Can you represent M_{XY}(s,t) in the form M_1(s) \cdot M_2(t)?

RGV

Is it 1/(1-2s) . 1/(1-3t)?
 
wannabe92 said:
Is it 1/(1-2s) . 1/(1-3t)?

Well, is it? You can answer your own question.

RGV
 
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