15 papers · ranked by Valyu relevance
Thomas A. Trikalinos, Yuliia Sereda, Abhik Ghosh
We introduce the nhppp package for simulating events from one dimensional non-homogeneous Poisson point processes (NHPPPs) in R fast and with a small memory footprint. We developed it to facilitate the sampling of event times in discrete event and statistical simulations. The package’s functions are based on three…
Andi Kresna Jaya, Nurtiti Sunusi, Erna Tri Herdiani
The point process model effectively represents the number of random events occurring over time through its intensity function. When events are of two types, a bivariate point process allows simultaneous analysis of each event’s intensity. This study develops a conditional intensity model for a non-homogeneous bivariate…
M. J. Faddy, A. N. Pettitt
Background We consider cluster size data of SARS-CoV-2 transmissions for a number of different settings from recently published data. The statistical characteristics of superspreading events are commonly described by fitting a negative binomial distribution to secondary infection and cluster size data as an alternative…
Xunqian Xu, Guozhi Wan, Fengyi Kang, Shue Li + 5 more
'Qi Li' 'Chen Lv' 'Simon Hesp'] The paving layer on the steel box girder bridge deck is widely used when constructing pavements for steel bridges. Owing to the orthotropic feature of steel decks, a transverse clapboard and rib can lead to a concentration of stress. Consequently, fatigue cracks are often identified in…
Sophie Jaffard, Giulia Mezzadri, Patricia Reynaud-Bouret, Etienne Tanré
In cognition, response times and choices in decision-making tasks are commonly modeled using Drift Diffusion Models (DDMs), which describe the accumulation of evidence for a decision as a stochastic process, specifically a Brownian motion, with the drift rate reflecting the strength of the evidence. In the same vein…
Joshua Corneck, Edward A. K. Cohen, James S. Martin, Francesco Sanna Passino
'Francesco Sanna Passino'] Network point processes often exhibit latent structure that govern the behaviour of the sub-processes. It is not always reasonable to assume that this latent structure is static, and detecting when and how this driving structure changes is often of interest. In this paper, we introduce a…
Sergey Vinogradov, Fabio Acerbi
This paper presents an order statistic approach to the time distribution of the first detected event following a primary avalanche pulse, considering a mixture of correlated and primary dark counts. The well-known order statistic method, commonly used to describe the time resolution of scintillation detectors, is…
Xuhua Xia, Daria Sanna
Classical branching-process theory, developed by Galton and Watson in the nineteenth century and later refined by Fisher and Haldane, provides the formal framework for quantifying the fate of new mutants, new viral and bacterial pathogens, new colonization of invasive species, etc. It is a powerful tool to quantify and…
Mikko S. Pakkanen, Xenia Miscouridou, Matthew J. Penn, Charles Whittaker + 4 more
'Charles Whittaker' 'Tresnia Berah' 'Swapnil Mishra' 'Thomas A. Mellan' 'Samir Bhatt'] Renewal equations are a popular approach used in modelling the number of new infections, i.e., incidence, in an outbreak. We develop a stochastic model of an outbreak based on a time-varying variant of the Crump-Mode-Jagers branching…
Juraj Szavits-Nossan, Ramon Grima
Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods. Here, we provide a tutorial review of an alternative approach based on queueing theory that has rarely been used in the literature of…
Isuru Panduka Ratnayake, V. A. Samaranayake, Cathy W. S. Chen
A serially dependent Poisson process with time-varying zero-inflation is proposed. Such formulations have the potential to model count data time series arising from phenomena such as infectious diseases that ebb and flow over time. The model assumes that the intensity of the Poisson process evolves according to a…
Lorenzo Facciaroni, Costantino Ricciuti, Enrico Scalas, Bruno Toaldo
There is a well-established theory that links semi-Markov chains having Mittag-Leffler waiting times to time-fractional equations. We here go beyond the semi-Markov setting, by defining some non-Markovian chains whose waiting times, although marginally Mittag-Leffler, are assumed to be stochastically dependent. This…
Kumar Utkarsh, Nirmish R. Shah, Tanvi Banerjee, Daniel M. Abrams + 1 more
Researchers across different fields, including but not limited to ecology, biology, and healthcare, often face the challenge of sparse data. Such sparsity can lead to uncertainties, estimation difficulties, and potential biases in modeling. Here we introduce a novel data augmentation method that combines multiple…
Philip K. Pollett, Laleh Tafakori, Peter G. Taylor
In mathematical biology, there is a great deal of interest in producing continuum models by scaling discrete agent-based models governed by local stochastic rules. We discuss a particular example of this approach: a model for the proliferation of neural crest cells that can help us understand the development of…
Joe Hilton, Ian Hall, Eric Lofgren
Outbreaks of emerging and zoonotic infections represent a substantial threat to human health and well-being. These outbreaks tend to be characterised by highly stochastic transmission dynamics with intense variation in transmission potential between cases. The negative binomial distribution is commonly used as a model…