Hi, Jerry,
Please see the FAQ: What's a reproducible example (`reprex`) and how do I do one? Using a reprex, complete with representative data will attract quicker and more answers. Also, in the reprex
it's good etiquette to use
require(deSolve) # in place of install.packages("deSolve")
The parameters are user selected arguments to the sir_values_1
function, which self destructs with
sir_values_1 <- as.data.frame(sir_values_1)
You probably want to do something like
run1 <- as.data.frame(sir_values_1)
So, to recover those
# require(deSolve) # in place of install.packages(deSolve)
### snip
parameters_values<- c(
beta = 0.001, # infectious contact rate (/person/day)
gamma = 0.015 # recovery rate (/day)
)
### snip
### added to show where to find beta and gamma parameters; none others used except for starting values
parameters_values
#> beta gamma
#> 0.001 0.015
Created on 2020-04-05 by the reprex package (v0.3.0)
The choice of which parameter values is domain specific. All assumptions within the permitted range of a function to be given as arguments are equally valid from a data science computational stance; whether they are equally reasonable is a matter of the analyst's judgment about the subject matter.
This community may have some epidemiologists from time-to-time, but I imagine that most of them are, sadly, too busy now to offer advice. I suggest moving the types of questions beyond the mechanics and going into the realm of subject matter expertise into more general online discussions.
Good luck! And, thanks for sharing Chimes
! Extremely interesting.
P.S. check out this page on the CHIME site