ccl4model {deSolve}  R Documentation 
The CCl4 inhalation model implemented in .Fortran
ccl4model(times, y, parms, ...)
times 
time sequence for which the model has to be integrated. 
y 
the initial values for the state variables ("AI", "AAM", "AT", "AF", "AL", "CLT" and "AM"), in that order. 
parms 
vector or list holding the ccl4 model parameters; see the example for the order in which these have to be defined. 
... 
any other parameters passed to the integrator ode
(which solves the model).

The model is implemented primarily to demonstrate the linking of FORTRAN with Rcode.
The source can be found in the ‘dynload’ subdirectory of the package.
R. Woodrow Setzer <setzer.woodrow@epa.gov>
Try demo(CCL4model)
for how this model has been fitted to the
dataset ccl4data,
aquaphy
, another Fortran model, describing growth in
aquatic phytoplankton.
## ================= ## Parameter values ## ================= Pm < c( ## Physiological parameters BW = 0.182, # Body weight (kg) QP = 4.0 , # Alveolar ventilation rate (hr^1) QC = 4.0 , # Cardiac output (hr^1) VFC = 0.08, # Fraction fat tissue (kg/(kg/BW)) VLC = 0.04, # Fraction liver tissue (kg/(kg/BW)) VMC = 0.74, # Fraction of muscle tissue (kg/(kg/BW)) QFC = 0.05, # Fractional blood flow to fat ((hr^1)/QC QLC = 0.15, # Fractional blood flow to liver ((hr^1)/QC) QMC = 0.32, # Fractional blood flow to muscle ((hr^1)/QC) ## Chemical specific parameters for chemical PLA = 16.17, # Liver/air partition coefficient PFA = 281.48, # Fat/air partition coefficient PMA = 13.3, # Muscle/air partition coefficient PTA = 16.17, # Viscera/air partition coefficient PB = 5.487, # Blood/air partition coefficient MW = 153.8, # Molecular weight (g/mol) VMAX = 0.04321671, # Max. velocity of metabolism (mg/hr) calibrated KM = 0.4027255, # MichaelisMenten constant (mg/l) calibrated ## Parameters for simulated experiment CONC = 1000, # Inhaled concentration KL = 0.02, # Loss rate from empty chamber /hr RATS = 1.0, # Number of rats enclosed in chamber VCHC = 3.8 # Volume of closed chamber (l) ) ## ================ ## State variables ## ================ y < c( AI = 21, # total mass , mg AAM = 0, AT = 0, AF = 0, AL = 0, CLT = 0, # area under the conc.time curve in the liver AM = 0 # the amount metabolized (AM) ) ## ================== ## Model application ## ================== times < seq(0, 6, by = 0.1) ## initial inhaled concentrationcalibrated conc < c(26.496, 90.197, 245.15, 951.46) plot(ChamberConc ~ time, data = ccl4data, xlab = "Time (hours)", xlim = range(c(0, ccl4data$time)), ylab = "Chamber Concentration (ppm)", log = "y", main = "ccl4model") for (cc in conc) { Pm["CONC"] < cc VCH < Pm[["VCHC"]]  Pm[["RATS"]]*Pm[["BW"]] AI0 < VCH * Pm[["CONC"]]*Pm[["MW"]]/24450 y["AI"] < AI0 ## run the model: out < as.data.frame(ccl4model(times, y, Pm)) lines(out$time, out$CP,lwd = 2) } legend("topright", lty = c(NA, 1), pch = c(1, NA), lwd = c(NA, 2), legend = c("data", "model"))