[HTML][HTML] Bivariate binomial autoregressive models
This paper introduces new classes of bivariate time series models being useful to fit count
data time series with a finite range of counts. Motivation comes mainly from the comparison …
data time series with a finite range of counts. Motivation comes mainly from the comparison …
On bivariate threshold Poisson integer-valued autoregressive processes
K Yang, Y Zhao, H Li, D Wang - Metrika, 2023 - Springer
To capture the bivariate count time series showing piecewise phenomena, we introduce a
first-order bivariate threshold Poisson integer-valued autoregressive process. Basic …
first-order bivariate threshold Poisson integer-valued autoregressive process. Basic …
Predicting US‐and state‐level cancer counts for the current calendar year: Part I: evaluation of temporal projection methods for mortality
HS Chen, K Portier, K Ghosh, D Naishadham, HJ Kim… - Cancer, 2012 - Wiley Online Library
BACKGROUND: A study was undertaken to evaluate the temporal projection methods that
are applied by the American Cancer Society to predict 4‐year‐ahead projections …
are applied by the American Cancer Society to predict 4‐year‐ahead projections …
Bayesian dynamic modeling of time series of dengue disease case counts
DA Martínez-Bello, A López-Quílez… - PLoS neglected …, 2017 - journals.plos.org
The aim of this study is to model the association between weekly time series of dengue case
counts and meteorological variables, in a high-incidence city of Colombia, applying …
counts and meteorological variables, in a high-incidence city of Colombia, applying …
Bayesian modeling of multivariate time series of counts
R Soyer, D Zhang - Wiley Interdisciplinary Reviews …, 2022 - Wiley Online Library
In this article, we present an overview of recent advances in Bayesian modeling and
analysis of multivariate time series of counts. We discuss basic modeling strategies …
analysis of multivariate time series of counts. We discuss basic modeling strategies …
Updated methodology for projecting US-and state-level cancer counts for the current calendar year: part II: evaluation of incidence and mortality projection methods
Abstract Background: The American Cancer Society (ACS) and the NCI collaborate every 5
to 8 years to update the methods for estimating the numbers of new cancer cases and …
to 8 years to update the methods for estimating the numbers of new cancer cases and …
Autoregressive and moving average models for zero‐inflated count time series
Zero inflation is a common nuisance while monitoring disease progression over time. This
article proposes a new observation‐driven model for zero‐inflated and over‐dispersed …
article proposes a new observation‐driven model for zero‐inflated and over‐dispersed …
Retrospective time series analysis of veterinary laboratory data: preparing a historical baseline for cluster detection in syndromic surveillance
The practice of disease surveillance has shifted in the last two decades towards the
introduction of systems capable of early detection of disease. Modern biosurveillance …
introduction of systems capable of early detection of disease. Modern biosurveillance …
Bayesian optimisation of restriction zones for bluetongue control
We investigate the restriction of animal movements as a method to control the spread of
bluetongue, an infectious disease of livestock that is becoming increasingly prevalent due to …
bluetongue, an infectious disease of livestock that is becoming increasingly prevalent due to …
Using Bayes' rule to define the value of evidence from syndromic surveillance
MG Andersson, C Faverjon, F Vial, L Legrand… - PloS one, 2014 - journals.plos.org
In this work we propose the adoption of a statistical framework used in the evaluation of
forensic evidence as a tool for evaluating and presenting circumstantial “evidence” of a …
forensic evidence as a tool for evaluating and presenting circumstantial “evidence” of a …