Probability Density Function of the Product of Independent Variables

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Discussion Overview

The discussion centers on finding the probability density function (PDF) of the product of two independent random variables, specifically when the variables are denoted as y = ab. Participants explore methods for deriving the PDF based on the known PDFs of the individual variables a and b, with considerations for cases where the variables may be zero.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant asks how to find the PDF of y = ab given the PDFs of a and b, noting familiarity with the method for the ratio a/b.
  • Another participant outlines a method involving the joint PDF of A and B, the cumulative distribution function (CDF) of Y, and differentiation to obtain the PDF of Y, while emphasizing the need for caution if A or B can be zero.
  • A similar method is reiterated by another participant, reinforcing the steps to express the joint PDF and calculate the CDF and PDF of Y, while also questioning the correctness of a previously mentioned formula for the PDF of A/B.
  • One participant acknowledges that the variables A and B were standard normal in the context of the A/B example but expresses uncertainty about whether they can claim A and B are standard normal variables.
  • A summary reiterates the initial question about finding the PDF of y = ab and mentions that A/B has a Cauchy distribution if A and B are standard normals.

Areas of Agreement / Disagreement

Participants present multiple competing views on the methods for deriving the PDF of the product of independent variables, and there is no consensus on the correctness of the approaches or the assumptions regarding the distributions of A and B.

Contextual Notes

Participants note that the integration methods must account for cases where A or B could be zero, which complicates the calculations. There is also uncertainty regarding the specific distributions of A and B, particularly whether they can be assumed to be standard normal.

megf
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How do I find the probabilty density function of a variable y being y=ab, knowing the probabilty density functions of both a and b?
How do I find the probability density function of a variable y being y=ab, knowing the probability density functions of both a and b? I know how to use the method to calculate it for a/b - which gives 1/pi*(a²/b²+1) - using variable substitution and the jacobian matrix and determinant, but which functions should i use for the product?
 
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Let the random variables be ##A## and ##B##, with density functions ##f_A## and ##f_B## respectively. Let ##Y=AB##. For simplicity, assume that ##A,B## can only be positive.
1. express the joint probability density function ##f_{A,B}## of the two variables in terms of ##f_A## and ##f_B##. Use the fact that they are independent.

2. calculate the cumulative distribution function of Y:
$$F_Y(y) = \int_{0}^\infty \int_{0}^{y/a} f_{A,B}(a,b)\, db\,da$$

3. Differentiate ##F_Y## to get ##f_Y##, the PDF of ##Y##.

If A or B can be zero, the solution needs to be more complex, to avoid divisions by zero. The integrations need to be split into parts that avoid zero.

By the way, the formula you provided for the PDF of A/B does not look right, as it contains no integrals. Have you omitted some info from the question, such as that the two variables are standard normal, or some other specific distribution?
 
andrewkirk said:
Let the random variables be ##A## and ##B##, with density functions ##f_A## and ##f_B## respectively. Let ##Y=AB##. For simplicity, assume that ##A,B## can only be positive.
1. express the joint probability density function ##f_{A,B}## of the two variables in terms of ##f_A## and ##f_B##. Use the fact that they are independent.

2. calculate the cumulative distribution function of Y:
$$F_Y(y) = \int_{0}^\infty \int_{0}^{y/a} f_{A,B}(a,b)\, db\,da$$

3. Differentiate ##F_Y## to get ##f_Y##, the PDF of ##Y##.

If A or B can be zero, the solution needs to be more complex, to avoid divisions by zero. The integrations need to be split into parts that avoid zero.

By the way, the formula you provided for the PDF of A/B does not look right, as it contains no integrals. Have you omitted some info from the question, such as that the two variables are standard normal, or some other specific distribution?

Oh, yes, they were standard normal in the A/B example I mentioned. My bad. Though I'm not sure if I can say my variables are standard normal variables.
 
megf said:
Summary: How do I find the probability density function of a variable y being y=ab, knowing the probability density functions of both a and b?

How do I find the probability density function of a variable y being y=ab, knowing the probability density functions of both a and b? I know how to use the method to calculate it for a/b - which gives 1/pi*(a²/b²+1) - using variable substitution and the jacobian matrix and determinant, but which functions should i use for the product?
If A, B are standard normals A/B has a Cauchy distribution.
 

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