Abstract: This article analyzes the stability of probabilistic Boolean networks (PBNs) with switching discrete probability distribution (DPD). First, the dynamics of PBNs with switching DPD is ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

In statistics, the expected value of a random variable is a measure of the central tendency of its probability distribution. In simple terms, it gives you an idea of what value you should expect to ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

In this paper, we use the generalized hypergeometric series method the high-order inverse moments and high-order inverse factorial moments of the generalized geometric distribution, the Katz ...

ABSTRACT: Empirical estimates of power and Type I error can be misleading if a statistical test does not perform at the stated rejection level under the null ...

Abstract: We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be ...