Ignoring the domain of RV in punif()
Before the ticket finally enters the waste bin, I think it is
necessary to explicitly explain what is meant by the "domain"
of a random variable. This is not (though in special cases
could be) the space of possible values of the random variable.
Definition of (real-valued) Random Variable (RV):
Let Z be a probability space, i.e. a set {z} of entities z
on which a probability distribution is defined. The entities z
do not need to be numeric. A real-valued RV X is a function
X:Z --> R defined on Z such that, for any z in Z, X(z) is a
real number. The set Z, in tthis context, is (by definitipon)
the *domain* of X, i.e. the space on which X is defined.
It may or may not be (and usually is not) the same as the set
of possible values of X.
Then. given any real value x0, the CDF of X at x- is Prob[X <= X0].
The distribution function of X does not define the domain of X.
As a simple exam[ple: Suppose Q is a cube of side A, consisting of
points z=(u,v,w) with 0 <= u,v,w <= A. Z is the probability space
of points z with a uniform distribution of position within Q.
Define the random variable X:Q --> [0,1] as
X(u,v,w) = x/A
Then X is uniformly distributed on [0,1], the domain of X is Q.
Then for x <= 0 _Prob[X <= x] = 0, for 0 <= x <= 1 Prob(X >=x] = x,
for x >= 1 Prob(X <= x] = 1. These define the CDF. The set of poaaible
values of X is 1-dimensional, and is not the same as the domain of X,
which is 3-dimensional.
Hopiong this helps!
Ted.
On Tue, 2018-10-23 at 10:54 +0100, Hamed Ha wrote:
Yes, now it makes more sense. Okay, I think that I am convinced and we can close this ticket. Thanks Eric. Regards, Hamed. On Tue, 23 Oct 2018 at 10:42, Eric Berger <ericjberger at gmail.com> wrote:
Hi Hamed, That reference is sloppy. Try looking at https://en.wikipedia.org/wiki/Cumulative_distribution_function and in particular the first example which deals with a Unif[0,1] r.v. Best, Eric On Tue, Oct 23, 2018 at 12:35 PM Hamed Ha <hamedhaseli at gmail.com> wrote:
Hi Eric, Thank you for your reply. I should say that your justification makes sense to me. However, I am in doubt that CDF defines by the Pr(x <= X) for all X? that is the domain of RV is totally ignored in the definition. It makes a conflict between the formula and the theoretical definition. Please see page 115 in https://books.google.co.uk/books?id=FEE8D1tRl30C&printsec=frontcover&dq=statistical+distribution&hl=en&sa=X&ved=0ahUKEwjp3PGZmJzeAhUQqxoKHV7OBJgQ6AEIKTAA#v=onepage&q=uniform&f=false The Thanks. Hamed. On Tue, 23 Oct 2018 at 10:21, Eric Berger <ericjberger at gmail.com> wrote:
Hi Hamed,
I disagree with your criticism.
For a random variable X
X: D - - - > R
its CDF F is defined by
F: R - - - > [0,1]
F(z) = Prob(X <= z)
The fact that you wrote a convenient formula for the CDF
F(z) = (z-a)/(b-a) a <= z <= b
in a particular range for z is your decision, and as you noted this
formula will give the wrong value for z outside the interval [a,b].
But the problem lies in your formula, not the definition of the CDF
which would be, in your case:
F(z) = 0 if z <= a
= (z-a)/(b-a) if a <= z <= b
= 1 if 1 <= z
HTH,
Eric
On Tue, Oct 23, 2018 at 12:05 PM Hamed Ha <hamedhaseli at gmail.com> wrote:
Hi All, I recently discovered an interesting issue with the punif() function. Let X~Uiform[a,b] then the CDF is defined by F(x)=(x-a)/(b-a) for (a<= x<= b). The important fact here is the domain of the random variable X. Having said that, R returns CDF for any value in the real domain. I understand that one can justify this by extending the domain of X and assigning zero probabilities to the values outside the domain. However, theoretically, it is not true to return a value for the CDF outside the domain. Then I propose a patch to R function punif() to return an error in this situations. Example:
punif(10^10)
[1] 1
Regards,
Hamed.
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