Can someone provide an example of X being a non-continuous random variable with continuous cumulative distribution function?
For instance:
X is discrete if it takes (at most) a countable number of values.
X is continuous (or absolutely continuous) if its law PX admits a density f(x).
Note: A random variable don't have to be necessarily discrete or continuous; just take a cumulative distribution function that is non-constant and continuous except in 0.
Then X is neither continuous nor discrete.
I know that to ensure that X is continuous, we need to ask FX∈C1, as FX∈C0 does not suffice.
I would then like to see a non continuous random variable with continuous cdf
Answer
A simple example is X uniformly distributed on the usual Cantor set, in other words, X=∑n⩾ for some i.i.d. sequence (Y_n) with uniform distribution on \{0,2\}.
Other examples are based on binary expansions, say, X=\sum_{n\geqslant1}\frac{Z_n}{2^n}, for some i.i.d. sequence (Z_n) with any nondegenerate distribution on \{0,1\} except the uniform one.
These distributions have no density with respect to Lebesgue measure, even partly, since P(X\in C)=1 for some Borel set C with zero Lebesgue measure. They have no atom either, in the sense that P(X=x)=0 for every x.
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