Once my professor told us in passing that a non-negative integrable (Riemann or Lebesgue) function that integrates to one over its support need not be a probability density function. I have since tried to find counterexamples where this is true, but have failed. Is there any such counterexample? Also, is there a theorem establishing sufficient conditions on a function to be a pdf?
Tell me more
×
Mathematics Stack Exchange is a question and answer site for
people studying math at any level and professionals in related fields. It's 100% free, no registration required.
|
|
If $f:\mathbb{R}\to \mathbb{R}$ is a Borel function that satisfies $f(x)\geq 0$ for all $x\in\mathbb{R}$ and $\int_\mathbb{R} f d\lambda =1$, then $$ P(A)=\int_A f d\lambda,\quad A\in \mathcal{B}(\mathbb{R}) $$ defines a probability meausure on $(\mathbb{R},\mathcal{B}(\mathbb{R}))$. Now let $(\Omega,\mathcal{F},P)=(\mathbb{R},\mathcal{B}(\mathbb{R}),P)$ be your probability space and define a random variable $X:\Omega \to \mathbb{R}$ by the identity mapping, i.e. $X(\omega)=\omega, \;\omega\in\Omega$. Then the distribution of $X$ is $P\circ X^{-1}=P$ which has density $f$. So I guess you would have to look at non-measureable functions $f$ to find your counterexample. |
|||||||||
|