fit_nlin: Fits epidemic models using nonlinear aproach

In AlvesKS/epifitter: Analysis and Simulation of Plant Disease Progress Curves

Fits epidemic models using nonlinear aproach

Description

Fits epidemic models (Exponential, Monomolecular, Logistic and Gompertz) using nonlinear approach for estimate parameters.

Usage

fit_nlin(time,
  y,
  starting_par = list(y0 = 0.01, r = 0.03),
  maxiter = 50)

Arguments

time	Numeric vector which refers to the time steps in the epidemics
y	Numeric vector which refers to the disease intensity
starting_par	Starting value for initial inoculun (y0) and apparent infection rate (r). Please informe in that especific order
maxiter	Maximun number of iterations

Author(s)

Kaique dos S. Alves

Examples

set.seed(1)
epi1 <- sim_logistic(N = 30,
                     y0 = 0.01,
                     dt = 5,
                     r = 0.3,
                     alpha = 0.5,
                     n = 4)
data = data.frame(time =  epi1[,2], y = epi1[,4])
fit_nlin(time = data$time, y =  data$y, starting_par = list(y0 = 0.001, r = 0.03), maxiter = 1024)

AlvesKS/epifitter documentation built on Jan. 26, 2025, 3:23 a.m.