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Overdispersion Effects on Reliability Test Planning [PDF]
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Pérez-González, Carlos J. +3 more
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Dealing with overdispersion in multivariate count data [PDF]
, 2022 The problem of overdispersion in multivariate count data is a challenging issue. It covers a central role mainly due to the relevance of modern technology-based data, such as Next Generation Sequencing and textual data from the web or digital collections.
Viroli C., Corsini N.
core +1 more source
Overdispersion in service systems
, 2020 In this thesis service systems with nonstandard arrival processes are studied. In order to mimic real arrival data, we choose to incorporate overdispersion in the models. This feature is abundantly present in (arrival) data of e.g., emergency departments and call centers and corresponds to the phenomenon that the variance of the number of arrivals is ...
Heemskerk, J.M.A.
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Intravenous thrombolysis (IVT) before thrombectomy for ischemic stroke may alter clot structure and procedural performance. We investigated how IVT relates to thrombectomy metrics across stroke etiologies. Methods We performed a time‐to‐event analysis of consecutive patients with anterior circulation large vessel occlusion (acLVO ...
Annahita Sedghi +8 more
wiley +1 more source
Peer Community JournalSpatially explicit capture–recapture models are used widely to estimate the density of animal populations. The population is represented by an inhomogeneous Poisson point process, where each point is the activity centre of an individual and density ...
Efford, Murray G., Fletcher, David
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective We aimed to construct and evaluate the first laboratory‐based frailty index (FI‐Lab) for predicting adverse outcomes in systemic lupus erythematosus (SLE) and to compare its predictive ability to that of an existing clinical FI. Methods We used data from a single‐center prospective cohort of adult patients with SLE whose baseline visit ...
Grace Burns +2 more
wiley +1 more source
Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Min, Aleksey, Czado, Claudia
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Journal of Statistical Software, 2017 Rgbp is an R package that provides estimates and verifiable confidence intervals for random effects in two-level conjugate hierarchical models for overdispersed Gaussian, Poisson, and binomial data.
Hyungsuk Tak, Joseph Kelly, Carl Morris
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Frontiers in Ecology and Evolution, 2023 IntroductionSpecies distribution in alpine areas is constrained by multiple abiotic and biotic stressors. This leads to discrepant assembly patterns between different locations and study objects as opposite niche-based processes—limiting similarity and ...
Wen-Yu Song +9 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source