[R-sig-ME] [FORGED] Subjecting data to differential equations deSolve
Rolf Turner
r@turner @end|ng |rom @uck|@nd@@c@nz
Thu Nov 7 23:01:50 CET 2019
Maybe I'm obtuse (some would say that there's no "maybe" about it! :-) )
but I cannot for the life of me see what this question has to do with
mixed models.
Why not ask it on plain vanilla r-help???
cheers,
Rolf Turner
On 8/11/19 2:12 AM, Torsten Hauffe wrote:
> Dear list,
>
> My apologies if this question doesn't fit the scope of the mailing list.
>
> I try to solve some differential equations with the deSolve::ode and need
> to feed some values at certain time-points into the equations.
>
> Anyone has a guess why the results are off by factor 10?
>
> Thanks for any input and cheers,
> Torsten
>
> Here is a simplified reproducible example:
>
> # Time of observations
> ObsTime <- c(1.9, 2.0, 2.1, 3.9, 4.0, 4.1, 9.9, 10.0, 10.1, 23.9, 24.0,
> 24.1)
>
> # Value of the observations
> Obs <- c(0, 6, 0, 0, 3, 0, 0, 3, 0, 0, 3, 0)
>
> # following the second example of ode(), it needs a function from where
> values could be obtained as function of time
> obs3Func <- approxfun(ObsTime, Obs, method = "constant", rule = 2)
>
> # Subjecting the time to the approx-function works
> obs3Func(ObsTime)
>
> # A simple function that I expect to return the cumulative sum of Obs (i.e.
> 15)
> Test_rhs <- function(t, x, parms, obsFunc)
> {
> with(as.list(c(parms, x)), {
> Sa <- obsFunc(t)
> list(Sa * s)
> })
> }
>
> Test <- ode(y = 0,
> times = seq(0, 65, by = 0.1),
> func = Test_rhs,
> parms = list(s = 1),
> obsFunc = obs3Func)
>
> # Using s = 1, the results are off (my expectation) by factor 10
> plot(Test)
>
> # With s = 10 the result is as expected but I don't know why
> Test2 <- ode(y = 0,
> times = seq(0, 65, by = 0.1),
> func = Test_rhs,
> parms = list(s = 1),
> obsFunc = obs3Func)
> plot(Test2)
> # Changepoints & values
> Time <- c(2, 4, 10, 24)
> abline(v = Time, lty = 2, col = "grey")
> points(ObsTime, cumsum(Obs), pch = 19)
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