nlmixr (version 1.1.1-2)

dynmodel: Fit a non-population dynamic model

Description

Fit a non-population dynamic model

Usage

dynmodel(system, model, evTable, inits, data, fixPars = NULL,
  method = c("Nelder-Mead", "L-BFGS-B", "PORT"),
  control = list(ftol_rel = 1e-06, maxeval = 999), squared = T)

Arguments

system

an RxODE object

model

a list of statistical meaurement models

evTable

an Event Table object

inits

initial values of system parameters

data

input data

fixPars

fixed system parameters

method

estimation method: choice of Nelder-Mead, L-BFGS-B, and PORT.

control

optional minimization control parameters

squared

if parameters be squared during estimation

Examples

# NOT RUN {
ode <- "
   dose=200;
   pi = 3.1415926535897931;

   if (t<=0) {
      fI = 0;
   } else {
      fI = F*dose*sqrt(MIT/(2.0*pi*CVI2*t^3))*exp(-(t-MIT)^2/(2.0*CVI2*MIT*t));
   }

   C2 = centr/V2;
   C3 = peri/V3;
   d/dt(centr) = fI - CL*C2 - Q*C2 + Q*C3;
   d/dt(peri)  =              Q*C2 - Q*C3;
"
sys1 <- RxODE(model = ode)


## ------------------------------------------------------------------------
dat <- invgaussian
mod <- cp ~ C2 + prop(.1)
inits <- c(MIT=190, CVI2=.65, F=.92)
fixPars <- c(CL=.0793, V2=.64, Q=.292, V3=9.63)
ev <- eventTable()
ev$add.sampling(c(0, dat$time))
(fit <- dynmodel(sys1, mod, ev, inits, dat, fixPars))

# }

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