Type II success runs of Bernoulli trials separated by a gap

TL;DR

This paper analyzes success runs in Bernoulli trials separated by gaps, deriving probability distributions, moments, and properties for the longest run, extending existing models to include gaps greater than one.

Contribution

It introduces new formulas and methods for the distribution of success runs separated by gaps in Bernoulli trials, generalizing previous work limited to gaps of size one.

Findings

Derived probability mass functions for success runs with gaps

Presented recurrence relations and generating functions for longest run distribution

Calculated mean, variance, and factorial moments for the longest success run

Abstract

We treat success runs of independent identically distributed Bernoulli trials (with success parameter $p$) distributed according to the Type II binomial distribution of order $k$. However, the success runs are separated by a gap $g\ge1$ (a failure followed by $g-1$ arbitrary outcomes). Most of the literature treats the case $g=1$ only. Our main results are expressions for the probability mass function (we present two derivations) and the distribution of the longest success run. We also present more concise expressions for previously published results for the factorial moments. We present results for the mean, variance, probability mass function and factorial moments for $\textrm{NB}_{\rm II}(k,g,r)$, the Type II negative binomial distribution of order $k$, where the number of success runs $r$ is fixed and the number of trials $n$ is variable. Let $L$ denote the length of the longest success run. We present a recurrence and generating function for the distribution of $L$ and derive expressions for the mean, variance and factorial moments of $L$.