This article is cited in
4 papers
Theoretical Backgrounds of Applied Discrete Mathematics
On extreme joint probabilities of $k$ events chosen from $n$ events
Yu. A. Zuev Bauman Moscow State Technical University, Moscow, Russia
Abstract:
An arbitrary probability space with
$n$ events is considered. All events have the same probability
$p$. No restrictions on correlations between the events are imposed and the events are considered simply as arbitrary subsets of measure
$p$ in the probability space. From the set of
$n$ events, all
$C_n^k$ subsets
$X$ consisting of
$k$ events are chosen, and for each such subset
$X$ the probability
$\mathsf P(X)$ of joint implementation of its
$k$ events is considered. The subset with the minimum probability
$\min_{X\colon|X|=k}\mathsf P(X)$ and the subset with the maximum probability
$\max_{X\colon|X|=k}\mathsf P(X)$ are selected. In the paper, exact boundaries for both probabilities are obtained. For minimum probability:
\begin{gather*}
\text{if}\ kp\le k-1,\quad\text{then}\quad 0\le\min_{X\colon|X|=k}\mathsf P(X)\le p;\\
\text{if}\ kp>k-1,\quad\text{then}\quad kp-k+1\le\min_{X\colon|X|=k}\mathsf P(X)\le p.
\end{gather*}
For maximum probability:
\begin{gather*}
\text{if}\ np<k-1,\quad\text{then}\quad 0\le\max_{X\colon|X|=k}\mathsf P(X)\le p;\\
\text{if}\ k-1\le np<k,\quad\text{then}\quad\frac{np-\lfloor np\rfloor}{C_n^k}\le\max_{X\colon|X|=k}\mathsf P(X)\le p;\\
\text{if}\ k\le np,\quad\text{then}\quad\frac{(\lfloor np\rfloor+1-np)C_{\lfloor np\rfloor}^k +(np-\lfloor np\rfloor) C_{\lfloor np\rfloor+1}^k}{C_n^k}\le\max_{X\colon|X|=k}\mathsf P(X)\le p.
\end{gather*}
Keywords:
event, probability, linear programming, optimum base.
UDC:
519.157
DOI:
10.17223/20710410/39/1