nlmixr (version 1.0.0-7)

configsaem: Configure an SAEM model

Description

Configure an SAEM model by generating an input list to the SAEM model function

Usage

configsaem(model, data, inits, mcmc = list(niter = c(200, 300), nmc = 3,
  nu = c(2, 2, 2)), ODEopt = list(atol = 1e-06, rtol = 1e-04, stiff = 1,
  transitAbs = 0), distribution = c("normal", "poisson", "binomial"),
  seed = 99, fixed = NULL, DEBUG = 0)

Arguments

model

a compiled saem model by gen_saem_user_fn()

data

input data

inits

initial values

mcmc

a list of various mcmc options

ODEopt

optional ODE solving options

distribution

one of c("normal","poisson","binomial")

seed

seed for random number generator

fixed

a character vector of fixed effect only parameters (no random effects attached) to be fixed

DEBUG

Integer determining if debugging is enabled.

Details

Fit a generalized nonlinear mixed-effect model by he Stochastic Approximation Expectation-Maximization (SAEM) algorithm

Examples

# NOT RUN {
library(nlmixr)

#ode <- "d/dt(depot) =-KA*depot;
#        d/dt(centr) = KA*depot - KE*centr;"
#m1 = RxODE(ode, modName="m1")
#ode <- "C2 = centr/V;
#      d/dt(depot) =-KA*depot;
#      d/dt(centr) = KA*depot - KE*centr;"
#m2 = RxODE(ode, modName="m2")

#Note: only use the '=' assignment, not the '<-' at this point

PKpars = function()
{
  CL = exp(lCL)
  V  = exp(lV)
  KA = exp(lKA)
  KE = CL / V
  #initCondition = c(0, KE - CL/V)
}
PRED = function() centr / V
PRED2 = function() C2

saem_fit <- gen_saem_user_fn(model=lincmt(ncmt=1, oral=T))
#saem_fit <- gen_saem_user_fn(model=m1, PKpars, pred=PRED)
#saem_fit <- gen_saem_user_fn(model=m2, PKpars, pred=PRED2)


#--- saem cfg
nmdat = theo_sd
model = list(saem_mod=saem_fit, covars="WT")
inits = list(theta=c(.05, .5, 2))
cfg   = configsaem(model, nmdat, inits)
cfg$print = 50

#cfg$Rfn = nlmixr:::Ruser_function_cmt
#dyn.load("m1.d/m1.so");cfg$Rfn = nlmixr:::Ruser_function_ode
fit = saem_fit(cfg)
df = simple.gof(fit)
xyplot(DV~TIME|ID, df, type=c("p","l"), lwd=c(NA,1), pch=c(1,NA), groups=grp)
fit
# }

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