Multi-step polynomial regression method to model and forecast malaria incidence.
Malaria is one of the most severe problems faced by the world even today. Understanding the causative factors such as age, sex, social factors, environmental variability etc. as well as underlying transmission dynamics of the disease is important for epidemiological research on malaria and its eradi...
Main Authors: | Chandrajit Chatterjee, Ram Rup Sarkar |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2009-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC2648889?pdf=render |
Similar Items
-
Model Building Methods for the Inverse Polynomial Regressions
by: Gamshadzahi, A.
Published: (1975) -
Forecasting COVID-19 Cases in Algeria using Logistic Growth and Polynomial Regression Models
by: Mohamed Lounis, et al.
Published: (2021-07-01) -
Application of Gaussian process regression to forecast multi-step ahead SPEI drought index
by: Porya Ghasemi, et al.
Published: (2021-12-01) -
COVID-19 Highest Incidence Forecast in Russia Based on Regression Model
by: Iosif Z. Aronov, et al.
Published: (2020-10-01) -
A comparison of heuristic methods for polynomial regression model induction
by: Gints Jekabsons, et al.
Published: (2008-03-01)