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