About: Accurate prediction of COVID-19 related indicators such as confirmed cases, deaths and recoveries play an important in understanding the spread and impact of the virus, as well as resource planning and allocation. In this study, we approach the prediction problem from a statistical perspective and predict confirmed cases and deaths on a provincial level. We propose the compound Dirichlet Multinomial distribution to estimate the proportion parameter of each province as mutually exclusive outcomes. Furthermore, we make an assumption of exponential growth of the total cummulative counts in order to predict future total counts. The outcomes of this approach is not only prediction. The variation of the proportion parameter is characterised by the Dirichlet distribution, which provides insight in the movement of the pandemic across provinces over time.   Goto Sponge  NotDistinct  Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

AttributesValues
type
value
  • Accurate prediction of COVID-19 related indicators such as confirmed cases, deaths and recoveries play an important in understanding the spread and impact of the virus, as well as resource planning and allocation. In this study, we approach the prediction problem from a statistical perspective and predict confirmed cases and deaths on a provincial level. We propose the compound Dirichlet Multinomial distribution to estimate the proportion parameter of each province as mutually exclusive outcomes. Furthermore, we make an assumption of exponential growth of the total cummulative counts in order to predict future total counts. The outcomes of this approach is not only prediction. The variation of the proportion parameter is characterised by the Dirichlet distribution, which provides insight in the movement of the pandemic across provinces over time.
Subject
  • Virology
  • Epidemiology
  • Mathematical modeling
  • Exponentials
  • Scientific modeling
  • Exponential family distributions
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software