Results 41 to 50 of about 174,276,385 (305)
Evaluation of predictive capability of Bayesian spatio-temporal models for Covid-19 spread
BMC Medical Research Methodology, 2023 Background Bayesian models have been applied throughout the Covid-19 pandemic especially to model time series of case counts or deaths. Fewer examples exist of spatio-temporal modeling, even though the spatial spread of disease is a crucial factor in ...
Andrew B. Lawson
doaj +1 more source
A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data
Entropy, 2023 Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming ...
Huaping Chen, Jiayue Zhang, Xiufang Liu
doaj +1 more source
Journal of Time Series AnalysisThis article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced.
Jiajie Kong, Robert Lund
openaire +2 more sources
Power estimation using simulations for air pollution time-series studies
Environmental Health, 2012 Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and ...
Winquist Andrea +3 more
doaj +1 more source
Forecasting Daily COVID-19 Case Counts Using Aggregate Mobility Statistics
Data, 2022 The COVID-19 pandemic has impacted the whole world profoundly. For managing the pandemic, the ability to forecast daily COVID-19 case counts would bring considerable benefit to governments and policymakers. In this paper, we propose to leverage aggregate
Bulut Boru, M. Emre Gursoy
doaj +1 more source
Forecasting, 2023 The COVID-19 pandemic has had a catastrophic effect on the healthcare system including organ transplants worldwide. The number of living donor transplants performed in the US was affected more significantly by the pandemic with a 22.6% decrease in counts
Supraja Malladi, Qiqi Lu
doaj +1 more source
Bayesian Forecasting for Time Series of Count Data
Procedia Computer Science, 2019 Abstract Time series of count data is not a widely studied research topic. This paper develops Bayesian forecasting method of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. To determine a forecasted value of an observation-driven integer valued autoregressive model, a series of ...
Rinda Nariswari, Herena Pudjihastuti
openaire +2 more sources
Modelling Time Series of Counts with Hysteresis
Statistica SinicaIn this article, we propose a novel model for time series of counts called the hysteretic Poisson autoregressive (HPART) model with thresholds by extending the linear Poisson autoregressive model into a nonlinear model. Unlike other approaches that bear the adjective ``hysteretic", our model incorporates a scientifically relevant controlling factor ...
Ma, Xintong, Li, Dong, Tong, Howell
openaire +2 more sources
Probabilistic reconciliation of count time series
International Journal of ForecastingForecast reconciliation is an important research topic. Yet, there is currently neither formal framework nor practical method for the probabilistic reconciliation of count time series. In this paper we propose a definition of coherency and reconciled probabilistic forecast which applies to both real-valued and count variables and a novel method for ...
Giorgio Corani +2 more
openaire +2 more sources
A Bayesian-Deep Learning Model for Estimating COVID-19 Evolution in Spain
Mathematics, 2021 This work proposes a semi-parametric approach to estimate the evolution of COVID-19 (SARS-CoV-2) in Spain. Considering the sequences of 14-day cumulative incidence of all Spanish regions, it combines modern Deep Learning (DL) techniques for analyzing ...
Stefano Cabras
doaj +1 more source