fit_nlin2: Fits epidemic models using nonlinear aproach. This function...

In epifitter: Analysis and Simulation of Plant Disease Progress Curves

Description

Fits epidemic models (Exponential, Monomolecular, Logistic and Gompertz) using nonlinear approach for estimate parameters. This function also estimates the maximum disease intensity parameter K.

Usage

fit_nlin2(time,
  y,
  starting_par = list(y0 = 0.01, r = 0.03, K =  0.8),
  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), and maximum disease intensity (K). Please informe in that especific order
maxiter	Maximun number of iterations.

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_nlin2(time = data$time,
          y =  data$y,
          starting_par = list(y0 = 0.01, r = 0.03, K = 1),
          maxiter = 1024)

epifitter documentation built on June 14, 2021, 5:08 p.m.