CDF Query: Conditional CDF of S

In summary, the conversation discusses the validity of an expression involving a random variable S, defined by a formula involving other random variables and constants. The conclusion is that the expression holds true, based on the assumption that H and S are mutually independent.
  • #1
nikozm
54
0
Hello.

I was wondering if the following is correct.

Let S= a*X/(b*X+c), where a,b,c are positive constants and X is a positive random variable. Also let H= h, where h is also a positive random variable (S and H are mutually independent).

Then, let F_{Z}(.) and f_{Z}(.) denote the CDF and PDF of Z, respectively. Thus, does the following holds true?

F_{S}(y) = ∫ F_{S|H}(a*X/(b*X+c) <= y | H) * f_{H}(h) dh.

Thank you in advance.
 
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  • #2
You say H and S are independent. In that case F_{S|H} = F{S}. Therefore the expression hold trivially.
 

1. What is a CDF query?

A CDF query is a type of statistical query that allows you to find the conditional cumulative distribution function (CDF) of a variable given a specific condition or set of conditions. It is used to analyze the relationship between variables and determine the probability of a certain outcome occurring.

2. How is the conditional CDF calculated?

The conditional CDF is calculated by dividing the number of observations that satisfy the given condition by the total number of observations. This gives the probability of the variable being less than or equal to a specific value, given the condition.

3. What is the difference between a CDF query and a regular CDF?

A regular CDF provides the probability that a random variable will be less than or equal to a specific value, while a CDF query calculates the probability of a variable being less than or equal to a value, given a specific condition or set of conditions.

4. How is a CDF query useful in data analysis?

A CDF query can help in analyzing the relationship between variables and determining the probability of a certain outcome occurring. It can also be used to identify patterns and trends in data, and make predictions about future occurrences.

5. What are some examples of when a CDF query would be used?

A CDF query can be used in various fields such as finance, marketing, and healthcare. For example, in finance, it can be used to analyze the probability of a stock's price being higher than a certain value given a specific market condition. In marketing, it can be used to determine the likelihood of a customer purchasing a product based on their demographic information. In healthcare, it can be used to predict the probability of a patient developing a certain disease based on their lifestyle choices.

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