Derive Convolution Expression for Z_PDF(z)

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    Convolution deriving
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Discussion Overview

The discussion revolves around deriving the expression for the probability density function (PDF) of the sum of two independent random variables, Z = X + Y. Participants explore the mathematical relationships and manipulations involved in this derivation, focusing on the convolution of the individual PDFs of X and Y.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants propose starting with the relationship Z_PDF(z)*|dz| = X_PDF(x)*|dx| * Y_PDF(y)*|dy| as a basis for deriving Z_PDF(z).
  • Others question the validity of this relationship, suggesting that it requires a proper integration of the joint PDF of X and Y over the appropriate region.
  • One participant emphasizes that the derivation must account for all combinations of x and y that sum to z, indicating that Z_PDF(z) cannot depend on just one pair of values.
  • There is a suggestion to express the convolution formula as a differential or partial differential equation, potentially using the cumulative distribution function as a starting point.
  • Some participants discuss the implications of transformations and the need for the PDF of the destination random variable to consider all contributing source values.
  • There is a proposal to define the integration limits correctly and to clarify the integration process, particularly regarding the relationship between x, y, and z.

Areas of Agreement / Disagreement

Participants express differing views on the initial steps of the derivation and the assumptions required for the relationships to hold. There is no consensus on the correct approach to derive Z_PDF(z), and multiple competing views remain throughout the discussion.

Contextual Notes

Participants highlight the need for careful consideration of integration limits and the definitions of the variables involved. The discussion reveals a lack of clarity in the integration process and the relationships between the random variables.

  • #61
As far as I can tell, you aren't presenting any logical arguments. You are conjecturing various formulas and asking for criticism of them. That's a permissible approach in the early stages of an investigation, but you should follow-up a conjecture by testing it with some simple examples instead of relying on my comments. it's ok to make conjectures by resorting to "magic" - such as writing down symbols like "dx/dx" without asking what they symbolize. But you should proceed to working specific examples that force you to make specific interpretations. (I'm about to get busy for a few days with the jobs of being executor of an estate, so I'm not going to have time to criticize a hundred different conjectures.) - In fact I just got a phone call and I must leave right now.
 
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  • #62
I think the essence here is that for multiple variables/dimensions we need to use line/surface integrals
and that it starts to make more sense to use the joint PDF of the source RV's.
XY_PDF(x,y)*sqrt(dx^2 + dy^2) = X_PDF(x)*|dx| * Y_PDF(y)*sqrt(1 + (dy/dx)^2)

Hm, maybe regular multidimensional integration comes in when considering inequalities, like Z < X+Y.

I'll keep exploring. Thanks for all help!
 

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