Marginal PDF Bounds: Calculating Integration Limits

In summary, the integration bounds for calculating the marginal PDF of two random variables are 0<=x1<=1 and 0<=x2<=2(1-x1). These bounds are the same as those stated in the conversation. When performing integrations on distributions, it is important to use bounds that restrict the integration to the specific areas of interest.
  • #1
fishies
1
0
Hey guys,

So I'm having trouble telling what the integration bounds should be when calculation the marginal PDF of two random variables.

So the joint PDF fX1,X2(x1,x2) is a constant C = 1 in the regions x1 and x2.
The regions are bound by 0<=x1<=1 and 0<=x2<=2(1-x1).

If the marginal PDFs are defined as:
fx1 = int(-inf,inf) fX1,X2(x1,x2)*dx2
fx2 = int(-inf,inf) fX1,X2(x1,x2)*dx1

what will the integration bounds be?

Thanks for your help,
Fishies
 
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  • #2
fishies said:
what will the integration bounds be?

Fishies

They will be the same as the bounds that you stated for x1 and x2. Is that what you're asking? The use of minus infinity to plus infinity in theorems involving the distribution of random variables is correct if we use the convention that the distributions are defined to be zero at places where they are otherwise "undefined". To actually perform the integrations on distributions given by algebraic expressions but restricted to finite areas, you must use bounds that restrict the integration to those areas.
 

1. What is a marginal PDF?

A marginal PDF (probability density function) is a mathematical function that describes the probability of a continuous random variable taking on a specific value. It is a way to represent the probability distribution of a single variable when considering multiple variables.

2. How do I calculate integration limits for marginal PDF bounds?

The integration limits for marginal PDF bounds can be calculated by setting the upper limit to infinity and the lower limit to negative infinity. This allows for the entire range of the variable to be considered in the calculation.

3. Why is it important to calculate integration limits for marginal PDF bounds?

Calculating integration limits for marginal PDF bounds is important because it allows for the accurate calculation of the probability of a specific value for a single variable. It also ensures that the total probability of all possible values for the variable is equal to 1.

4. Can integration limits for marginal PDF bounds change?

Yes, integration limits for marginal PDF bounds can change depending on the specific variable being considered and the given situation. For example, if the variable is constrained to a certain range, the integration limits would need to be adjusted accordingly.

5. What are some applications of marginal PDF bounds?

Marginal PDF bounds have many applications in various fields such as statistics, economics, and physics. They are used to analyze and model data, make predictions, and understand the probability distribution of a single variable in relation to multiple variables.

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