Covariance between eta.Cl and eta.Vc in RxODE? #487
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newname2023
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Hi @newname2023 In general with omega <- lotri(eta.Cl + etaV ~ sd(cor(3, 0.95, 0.25))) And then simulate/solve s <- rxSolve(model, params, events, omega=omega) Of course if you use the new pheno <- function() {
ini({
tcl <- log(0.008) # typical value of clearance
tv <- log(0.6) # typical value of volume
## var(eta.cl)
eta.cl + eta.v ~ c(1,
0.01, 1) ## cov(eta.cl, eta.v), var(eta.v)
# interindividual variability on clearance and volume
add.err <- 0.1 # residual variability
})
model({
cl <- exp(tcl + eta.cl) # individual value of clearance
v <- exp(tv + eta.v) # individual value of volume
ke <- cl / v # elimination rate constant
d/dt(A1) = - ke * A1 # model differential equation
cp = A1 / v # concentration in plasma
cp ~ add(add.err) # define error model
})
}
f <- rxSolve(pheono, events) |
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Dear Dr. @mattfidler and nlmixr team,
Thanks for the useful package. I am learning your package for my modeling project and I have a problem. I don't know how to bring covariance or correlation between eta.Cl and eta.V in the code model? You can help me. Many thanks.
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