[R-sig-ME] Subjecting data to differential equations deSolve

[Torsten Hauffe]

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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