Fits epidemic models using nonlinear aproach. This function also estimates the maximum disease intensity parameter K

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

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)
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Warning: NaNs produzidos
#> Results of fitting population models 
#> 
#> Stats:
#>                  CCC r_squared    RSE
#> Gompertz      0.9950    0.9909 0.0438
#> Logistic      0.9923    0.9860 0.0539
#> Monomolecular 0.8960    0.8361 0.1797
#> 
#>  Infection rate:
#>                Estimate  Std.error      Lower      Upper
#> Gompertz      0.2630455 0.02071581 0.22038054 0.22038054
#> Logistic      0.3661332 0.03408759 0.29592845 0.29592845
#> Monomolecular 0.0682291 0.02690929 0.01280837 0.01280837
#> 
#>  Initial inoculum:
#>                    Estimate    Std.error         Lower        Upper
#> Gompertz       1.017021e-12 7.351869e-12 -1.412444e-11 1.615848e-11
#> Logistic       5.304329e-03 2.520782e-03  1.126822e-04 1.049598e-02
#> Monomolecular -1.487701e-01 8.495704e-02 -3.237424e-01 2.620220e-02
#> 
#>  Maximum disease intensity:
#>               Estimate  Std.error     Lower    Upper
#> Gompertz             1 0.01936234 0.9601225 1.039877
#> Logistic             1 0.02080931 0.9571424 1.042858
#> Monomolecular        1 0.19490764 0.5985802 1.401420