Assign residual error model to model object
residualError.Rd
Use to change or update residual error model for model object
Usage
residualError(
.Object,
predName = "C",
errorType = NULL,
SD = NULL,
isFrozen = FALSE,
isBQL = FALSE,
staticLLOQ = NULL,
EObsBQL = NULL,
CObsBQL = NULL,
C1ObsBQL = NULL,
A0ObsBQL = NULL,
exponent = NULL
)
Arguments
- .Object
Model object
- predName
Name of the predicted variable as returned in
residualEffectNames
.- errorType
Options are
"Additive"
,"LogAdditive"
,"Multiplicative"
,"AdditiveMultiplicative"
,"MixRatio"
,"Power"
.- SD
Value for the standard deviation of the residual error variable.
- isFrozen
Set to
TRUE
to freeze the standard deviation to the value specified forSD
.- isBQL
Set to
TRUE
if BQL values present in the observation data.- staticLLOQ
Optional LLOQ value if
isBQL = TRUE
- EObsBQL
Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to
EObs
. Only applicable toisBQL = TRUE
.- CObsBQL
Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to
CObs
. Only applicable toisBQL = TRUE
.- C1ObsBQL
Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to
C1Obs
. Only applicable toisBQL = TRUE
.- A0ObsBQL
Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to
AObs
. Only applicable toisBQL = TRUE
.- exponent
Value of exponent. Only applicable to
errorType = "Power"
.
Examples
model <- pkindirectmodel(indirectType = "LimitedInhibition", isBuildup = FALSE,
data = pkpdData, ID = "ID", Time = "Time", A1 = "Dose", CObs = "CObs", EObs = "EObs")
# Change error type to "Multiplicative" and value of SD to 0.1 for "E"
model <- residualError(model, predName = "E", errorType = "Multiplicative", SD = 0.1)
# Change error type to "Power", value of SD to 0.15, and set exponent = 2 for "C"
model <- residualError(model, predName = "C", errorType = "Power", SD = 0.15, exponent = 2)