A skew logistic distribution with application to modelling COVID-19 epidemic waves

01/31/2022
by   Mark Levene, et al.
0

A novel yet simple extension of the symmetric logistic distribution is proposed by introducing a skewness parameter. It is shown how the three parameters of the ensuing skew logistic distribution may be estimated using maximum likelihood. The skew logistic distribution is then extended to the skew bi-logistic distribution to allow the modelling of multiple waves in epidemic time series data. The proposed model is validated on COVID-19 data from the UK.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/21/2020

A Relationship Between SIR Model and Generalized Logistic Distribution with Applications to SARS and COVID-19

This paper shows that the generalized logistic distribution model is der...
research
06/09/2021

Spatial modelling of COVID-19 incident cases using Richards' curve: an application to the Italian regions

We introduce an extended generalised logistic growth model for discrete ...
research
03/21/2022

Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting

The long duration of the COVID-19 pandemic allowed for multiple bursts i...
research
09/26/2019

A bivariate logistic regression model based on latent variables

Bivariate observations of binary and ordinal data arise frequently and r...
research
04/11/2022

An extended Rayleigh model: Properties, regression and COVID-19 application

We define a four-parameter extended Rayleigh distribution, and obtain se...

Please sign up or login with your details

Forgot password? Click here to reset