Results 1 to 10 of about 290,245 (143)
SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics [PDF]
Nature Communications, 2023 Recent advancements in spatial transcriptomic technologies have enabled the measurement of whole transcriptome profiles with preserved spatial context. However, limited by spatial resolution, the measured expressions at each spot are often from a mixture
Zhiyuan Liu +3 more
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How to deal with the Poisson-gamma model to forecast patients' recruitment in clinical trials when there are pauses in recruitment dynamic? [PDF]
Contemporary Clinical Trials Communications, 2017 Recruiting patients is a crucial step of a clinical trial. Estimation of the trial duration is a question of paramount interest. Most techniques are based on deterministic models and various ad hoc methods neglecting the variability in the recruitment ...
Nathan Minois +4 more
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Risks, 2020 This article presents the Poisson-Inverse Gamma regression model with varying dispersion for approximating heavy-tailed and overdispersed claim counts. Our main contribution is that we develop an Expectation-Maximization (EM) type algorithm for maximum ...
George Tzougas
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A time‐dependent Poisson‐Gamma model for recruitment forecasting in multicenter studies [PDF]
Statistics in Medicine, 2023 Forecasting recruitments is a key component of the monitoring phase of multicenter studies. One of the most popular techniques in this field is the Poisson‐Gamma recruitment model, a Bayesian technique built on a doubly stochastic Poisson process.
David Stephens +2 more
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A more reliable species richness estimator based on the Gamma–Poisson model [PDF]
PeerJ, 2023 Background Accurately estimating the true richness of a target community is still a statistical challenge, particularly in highly diverse communities. Due to sampling limitations or limited resources, undetected species are present in many surveys and ...
Chun-Huo Chiu
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A Poisson-Gamma Model for Zero Inflated Rainfall Data
Journal of Probability and Statistics, 2018 Rainfall modeling is significant for prediction and forecasting purposes in agriculture, weather derivatives, hydrology, and risk and disaster preparedness.
Nelson Christopher Dzupire +2 more
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APPLICATION OF POISSON PROCESS TO DROUGHT PREDICTION – THE CASE STUDY OF YUCHENG CITY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Open-source R language can implement quantitative research using the flexibility, adaptability and simplicity of bayesian inference models. Counts of drought which are regarded as the realizations of drought “event” in a Poisson process follows an Gamma ...
Y. Yang, Y. Song
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Biometrics, 2021 We analyze predictions of future recruitment to a multicenter clinical trial based on a maximum‐likelihood fitting of a commonly used hierarchical Poisson–gamma model for recruitments at individual centers. We consider the asymptotic accuracy of quantile
R. Mountain, C. Sherlock
semanticscholar +1 more source
Mathematics, 2021 Most existing flexible count distributions allow only approximate inference when used in a regression context. This work proposes a new framework to provide an exact and flexible alternative for modeling and simulating count data with various types of ...
Chénangnon Frédéric Tovissodé +3 more
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Bayesian Estimation of Parameters Correlation of Bivariate Poisson Distribution [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2016 In this study, based on Bayesian Generalized Linear Models, correlation between the parameters of two Poisson distributions was computed. Due to lack of the closed form for posterior distribution, hierarchical Bayesian statistics using the Metropolis ...
Farzad Eskandari
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