Assign covariates for piping
Arguments
- covariates
NULL (for no covariates), or the list of covariates. nlmixr uses this function to set covariates if you pipe from a nlmixr fit.
Examples
# First set the name of known covariates
# Note this is case sensitive
rxSetCovariateNamesForPiping(c("WT","HT", "TC"))
one.compartment <- function() {
ini({
tka <- 0.45 ; label("Log Ka")
tcl <- 1 ; label("Log Cl")
tv <- 3.45 ; label("Log V")
eta.ka ~ 0.6
eta.cl ~ 0.3
eta.v ~ 0.1
add.err <- 0.7
})
model({
ka <- exp(tka + eta.ka)
cl <- exp(tcl + eta.cl)
v <- exp(tv + eta.v)
d / dt(depot) <- -ka * depot
d/dt(depot) <- -ka * depot
d / dt(center) <- ka * depot - cl / v * center
cp <- center / v
cp ~ add(add.err)
})
}
# now TC is detected as a covariate instead of a population parameter
one.compartment %>%
model({ka <- exp(tka + eta.ka + TC * cov_C)})
#>
#>
#> ℹ add covariate `TC` (known covariate)
#> ℹ add population parameter `cov_C` and set estimate to 1
#> ── rxode2-based free-form 2-cmt ODE model ──────────────────────────────────────
#> ── Initalization: ──
#> Fixed Effects ($theta):
#> tka tcl tv add.err cov_C
#> 0.45 1.00 3.45 0.70 1.00
#>
#> Omega ($omega):
#> eta.ka eta.cl eta.v
#> eta.ka 0.6 0.0 0.0
#> eta.cl 0.0 0.3 0.0
#> eta.v 0.0 0.0 0.1
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 depot
#> 2 2 center
#> ── μ-referencing ($muRefTable): ──
#> theta eta level covariates
#> 1 tka eta.ka id TC*cov_C
#> 2 tcl eta.cl id
#> 3 tv eta.v id
#>
#> ── Model (Normalized Syntax): ──
#> function() {
#> ini({
#> tka <- 0.45
#> label("Log Ka")
#> tcl <- 1
#> label("Log Cl")
#> tv <- 3.45
#> label("Log V")
#> add.err <- c(0, 0.7)
#> cov_C <- 1
#> eta.ka ~ 0.6
#> eta.cl ~ 0.3
#> eta.v ~ 0.1
#> })
#> model({
#> ka <- exp(tka + eta.ka + TC * cov_C)
#> cl <- exp(tcl + eta.cl)
#> v <- exp(tv + eta.v)
#> d/dt(depot) <- -ka * depot
#> d/dt(depot) <- -ka * depot
#> d/dt(center) <- ka * depot - cl/v * center
#> cp <- center/v
#> cp ~ add(add.err)
#> })
#> }
# You can turn it off by simply adding it back
rxSetCovariateNamesForPiping()
one.compartment %>%
model({ka <- exp(tka + eta.ka + TC * cov_C)})
#>
#>
#> ℹ add population parameter `TC` and set estimate to 1
#> ℹ add population parameter `cov_C` and set estimate to 1
#> ── rxode2-based free-form 2-cmt ODE model ──────────────────────────────────────
#> ── Initalization: ──
#> Fixed Effects ($theta):
#> tka tcl tv add.err TC cov_C
#> 0.45 1.00 3.45 0.70 1.00 1.00
#>
#> Omega ($omega):
#> eta.ka eta.cl eta.v
#> eta.ka 0.6 0.0 0.0
#> eta.cl 0.0 0.3 0.0
#> eta.v 0.0 0.0 0.1
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 depot
#> 2 2 center
#> ── μ-referencing ($muRefTable): ──
#> theta eta level
#> 1 tka eta.ka id
#> 2 tcl eta.cl id
#> 3 tv eta.v id
#>
#> ── Model (Normalized Syntax): ──
#> function() {
#> ini({
#> tka <- 0.45
#> label("Log Ka")
#> tcl <- 1
#> label("Log Cl")
#> tv <- 3.45
#> label("Log V")
#> add.err <- c(0, 0.7)
#> TC <- 1
#> cov_C <- 1
#> eta.ka ~ 0.6
#> eta.cl ~ 0.3
#> eta.v ~ 0.1
#> })
#> model({
#> ka <- exp(tka + eta.ka + TC * cov_C)
#> cl <- exp(tcl + eta.cl)
#> v <- exp(tv + eta.v)
#> d/dt(depot) <- -ka * depot
#> d/dt(depot) <- -ka * depot
#> d/dt(center) <- ka * depot - cl/v * center
#> cp <- center/v
#> cp ~ add(add.err)
#> })
#> }
# The covariates you set with `rxSetCovariateNamesForPiping()`
# are turned off every time you solve (or fit in nlmixr)