Transform Probability Distribution P to Uniform Distribution

  • Thread starter Thread starter mjpam
  • Start date Start date
  • Tags Tags
    Theorem
Click For Summary
A theorem states that a probability distribution P can be transformed into a uniform distribution using a specific transformation. The discussion references inverse transform sampling as a method for this conversion. However, it notes that while a continuous probability distribution can be transformed to a uniform distribution, the continuity of P is crucial for the reverse transformation. For discrete distributions, a transformation can exist from a discrete probability distribution P_D to a discrete uniform distribution U_D, with a well-defined inverse. The conversation emphasizes the importance of continuity in these transformations.
mjpam
Messages
79
Reaction score
0
I vaguely remember a theorem that says, given a probability distribution P, there exists a transform T from P to the uniform (I think discrete or continuous) distribution.

Is this true?

Can anyone provide me with an online citation?
 
Physics news on Phys.org
The uniform distribution can be transformed to any other distribution via the quantile function (i.e. the inverse CDF) but for the reverse the distribution must be continuous (a continuous interval can be mapped to a point but not vice-versa).
 
Would it be true to say thatm given a discrete probability distribution, P_{D}, and the discrete uniform distribution, U_{D} there exists transform
T : P_{D} \to U_{D} and its inverse T^{-1} is well-deifned?
 
If there are an infinite number of natural numbers, and an infinite number of fractions in between any two natural numbers, and an infinite number of fractions in between any two of those fractions, and an infinite number of fractions in between any two of those fractions, and an infinite number of fractions in between any two of those fractions, and... then that must mean that there are not only infinite infinities, but an infinite number of those infinities. and an infinite number of those...

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 31 ·
2
Replies
31
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 13 ·
Replies
13
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K