Graduate How to transform a probability density function?

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To transform the given probability density function f(x) into a new function g(x) with specified support, a linear transformation is applied. The transformation maps the original interval [0, 3π] to the new interval [(3/2)π, (15/2)π]. The resulting function g(x) is derived as g(x) = (1/2) * (1 / ((3/2) * π)) * (sin((1/2) * (x - (3/2) * π)))². Interestingly, g(x) coincides with another function h(x) = (1 / (6 * π)) * (sin(x) + 1) over the same interval, despite g(x) being quadratic and h(x) not. The discussion raises questions about the nature of these coinciding functions and their mathematical properties.
Ad VanderVen
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Transforming a trimodal probability density function with support [0;3*Pi] to a trimodal probability density function with support [(3/2)*Pi;(15/2)*Pi] .
I have the following probability density function (in Maple notation):

f (x) = (1 / ((3/2) * Pi)) * (sin (x)) ** 2 with support [0; 3 * Pi]

Now I want to transform x so that

0 -> (3/2) * Pi
and
3 * Pi -> (15/2) * Pi

and the new function is still a probability density function.

How should I do that transformation?
 
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Hi,
Ad VanderVen said:
0 -> (3/2) * Pi
and
3 * Pi -> (15/2) * Pi
It is a simple linear transformation.
So if we define ##x_0=0,\ x_1 = {3\over 2}\pi,\quad x_0'= 3\pi,\ x_1'={15\over2}\pi \;,\ ## then: $$x'= {x-x_0\over x_1-x_0} (x_1'-x'_0) \ \ {\sf and} \ \ dx'= {x'_1-x'_0\over x_1-x_0}\ dx$$

So you substitute ##\displaystyle {x = {x' - x_0'\over x_1'-x_0'}(x_1-x_0)}## and

with a simple factor ##{dx/ dx'}## you preserve the integral.

1591797960062.png
 
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Thanks a lot for your clear answer.

I have performed the transformation and I got (in Maple notation):

g (x) = (1/2) * (1 / ((3/2) * Pi)) * (sin ((1/2) * (x- (3/2) * Pi))) ** 2

with support [(3/2) * Pi; (15/2) * Pi)]

but this function coincides completely with the following function:

h (x) = (1 / (6 * Pi)) * (sin (x) +1)

also with support [(3/2) * Pi; (15/2) * Pi)]

Now g (x) is a quadratic function and h (x) is not. How can they coincide?
 
sin2(x) = 1/2*(1 - cos(2x))
 
Thank you very much. :bow:
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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