Approximation of Sums of Locally Dependent Random Variables via Perturbation of Stein Operator
Abstract: Let $(X_{i}, i\in J)$ be a family of locally dependent nonnegative integer-valued random variables, and consider the sum $W=\sum\nolimits_{i\in J}X_i$. We first establish a general error upper bound for $d_{TV}(W, M)$ using Stein's method, where the target variable $M$ is either the mixture of Poisson distribution and binomial or negative binomial distribution. As applications, we attain $O(|J|{-1})$ error bounds for ($k_{1},k_{2}$)-runs and $k$-runs under some special cases. Our results are significant improvements of the existing results in literature, say $O(|J|{-0.5})$ in Pek\"{o}z [Bernoulli, 19 (2013)] and $O(1)$ in Upadhye, et al. [Bernoulli, 23 (2017)].
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.