How to generally express a shifted PDF ?

  • Context: Undergrad 
  • Thread starter Thread starter nikozm
  • Start date Start date
  • Tags Tags
    Pdf
Click For Summary
SUMMARY

The discussion focuses on expressing the probability density function (PDF) of a transformed variable, specifically y = c x, in terms of the original PDF fx(x). The correct transformation is established as fy(y) = fx(y/c)/c. The conversation emphasizes the utility of the cumulative distribution function (CDF) for this transformation, where F(x) is defined as the integral of fx(t) from 0 to x. The relationship between the CDF and PDF is clarified through differentiation and manipulation of integrals.

PREREQUISITES
  • Understanding of probability density functions (PDFs)
  • Familiarity with cumulative distribution functions (CDFs)
  • Knowledge of integral calculus
  • Basic concepts of random variable transformations
NEXT STEPS
  • Study the properties of cumulative distribution functions (CDFs)
  • Learn about transformations of random variables in probability theory
  • Explore the relationship between differentiation and integration in probability
  • Investigate examples of shifted PDFs in statistical applications
USEFUL FOR

Statisticians, data scientists, and anyone involved in probability theory or statistical modeling will benefit from this discussion, particularly those working with transformed random variables and their distributions.

nikozm
Messages
51
Reaction score
0
Hello,

i am trying to solve the following.

Given a general PDF (i.e., fx(x), where x ≥ 0), how can i express the PDF of y = c x in terms of fx(x)?

I think that goes like this: fy(y) = fx(y/c)/c, but i 'm not sure.

Any help would be useful.

Thanks in advance
 
Physics news on Phys.org
nikozm, it's best to work with the CDF and then convert to the PDF. Let
[tex]F(x) = \int_{0}^{x} f_x(t) dt[/tex]

Then
[tex]P(y<M) = P(cx < M) = P(x < M/c) = F(M/c)[/tex]
So
[tex]P(y<M) = \int_{0}^{M/c} f_x(t) dt[/tex]
To find the pdf you just need to do some manipulations to the integral so that you have an [itex]\int_{0}^{M}[/itex], alternatively you can differentiate with respect to M to get the PDF.
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 12 ·
Replies
12
Views
5K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
2
Views
3K
  • · Replies 5 ·
Replies
5
Views
9K