How to generally express a shifted PDF ?

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To express the probability density function (PDF) of y = c x in terms of the original PDF fx(x), the cumulative distribution function (CDF) approach is recommended. By defining F(x) as the integral of fx(t) from 0 to x, the relationship P(y < M) can be established as P(cx < M), leading to P(x < M/c) = F(M/c). To derive the PDF fy(y), one must manipulate the integral or differentiate with respect to M. This method effectively transitions from the CDF back to the PDF.
nikozm
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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
 
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nikozm, it's best to work with the CDF and then convert to the PDF. Let
F(x) = \int_{0}^{x} f_x(t) dt

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