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I have a system of ODE equations that I am trying to fit to generated data, synthetic or lab. The final product I am interested in is the parameter and it's estimated error. We use the R package FME with modCost and modFit. As an example, a system of ODEs may be defined as such:

eqs <- function (time, y, parms, ...) {
  with(as.list(c(parms, y)), {
     dP <- k2*PA - k1*A*P  # concentration of nucleic acid
     dA <- dP  # concentration of free protein
     dPA <- -dP
list(c(dA,dP,dPA))
}
}

with parameters k1 and k2 and variables A,P and PA. I import the data (not shown) and define the cost function used in modFit 

cost <- function(p, data, ...) {
  yy <- p[c("A","P","PA")]
  pp <- p[c("k1", "k2")]
  out <- ode(yy, time, eqs, pp)
  modCost(out, data, ...)
}

I set some initial conditions with a parms vector and then do the fitting with 

fit <- modFit(f = cost, p = parms, data = dat, weight = "std", 
    lower = rep(0, 8), upper = c(600,100,600,0.01,0.01), method = "Marq")

I then do a final ode to get the generated fits with best parameters, Bob's your uncle, and boom, estimated parameters. The input numbers don't matter, I hope my process outline is legible for those who use this package.

My issue and question centers around two things: I'm a scientist, a physicist, and the error of the estimated parameters is important to report. Can I generate the estimated error from MFE somehow or is there a separate package for that kind of return?

Pentaquark
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    If this isn't working as you expect, then you need to post data and any error reports. – IRTFM Jun 06 '18 at 23:16

1 Answers1

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I don't get your point. You can just use:

summary(fit)

to see the Std. Error.

J_F
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  • A detailled explanation is found in the package vignette or in the following paper: https://doi.org/10.18637/jss.v033.i03 – tpetzoldt Jan 13 '20 at 06:45