Fit a generalized nonlinear mixed-effect model

Fit a generalized nonlinear mixed-effect model by adaptive Gaussian quadrature (AQD)

gnlmm(
  llik,
  data,
  inits,
  syspar = NULL,
  system = NULL,
  diag.xform = c("sqrt", "log", "identity"),
  ...,
  control = list()
)

gnlmm2(
  llik,
  data,
  inits,
  syspar = NULL,
  system = NULL,
  diag.xform = c("sqrt", "log", "identity"),
  ...,
  control = list()
)

Arguments

llik

log-likelihood function

data

data to be fitted

inits

initial values

syspar

function: calculation of PK parameters

system

an optional (compiled) RxODE object

diag.xform

transformation to diagonal elements of OMEGA during fitting

...

additional options

control

additional optimization options

Value

gnlmm fit object

Details

Fit a generalized nonlinear mixed-effect model by adaptive Gaussian quadrature (AGQ)

Author

Wenping Wang

Examples

# \donttest{
if (FALSE) {
llik <- function() {
  lp <- THETA[1] * x1 + THETA[2] * x2 + (x1 + x2 * THETA[3]) * ETA[1]
  p <- pnorm(lp)
  dbinom(x, m, p, log = TRUE)
}
inits <- list(THTA = c(1, 1, 1), OMGA = list(ETA[1] ~ 1))

try(gnlmm(llik, rats, inits, control = list(nAQD = 1)))

llik <- function() {
  if (group == 1) {
    lp <- THETA[1] + THETA[2] * logtstd + ETA[1]
  } else {
    lp <- THETA[3] + THETA[4] * logtstd + ETA[1]
  }
  lam <- exp(lp)
  dpois(y, lam, log = TRUE)
}
inits <- list(THTA = c(1, 1, 1, 1), OMGA = list(ETA[1] ~ 1))

fit <- try(gnlmm(llik, pump, inits,
  control = list(
    reltol.outer = 1e-4,
    optim.outer = "nmsimplex",
    nAQD = 5
  )
))



ode <- "
d/dt(depot) =-KA*depot;
d/dt(centr) = KA*depot - KE*centr;
"
sys1 <- RxODE(ode)

pars <- function() {
  CL <- exp(THETA[1] + ETA[1]) # ; if (CL>100) CL=100
  KA <- exp(THETA[2] + ETA[2]) # ; if (KA>20) KA=20
  KE <- exp(THETA[3])
  V <- CL / KE
  sig2 <- exp(THETA[4])
}
llik <- function() {
  pred <- centr / V
  dnorm(DV, pred, sd = sqrt(sig2), log = TRUE)
}
inits <- list(THTA = c(-3.22, 0.47, -2.45, 0))
inits$OMGA <- list(ETA[1]+ETA[2]~c(.027, .01, .37))

theo <- theo_md

fit <- try(gnlmm(llik, theo, inits, pars, sys1,
  control = list(trace = TRUE, nAQD = 1)
))

fit2 <- try(gnlmm2(llik, theo, inits, pars, sys1,
  control = list(trace = TRUE, nAQD = 1)
))

if (inherits(fit, "gnlmm.fit")) {
 cv <- calcCov(fit)
 cbind(fit$par[fit$nsplt == 1], sqrt(diag(cv)))
}
}
# }