Usage
drm(formula, curve, pmodels, weights, data = NULL, subset, fct,
adjust = c("none", "bc1", "bc2", "vp"), bc = NULL, bcAdd = 0,
type = c("continuous", "binomial", "Poisson", "survival"),
start, na.action = na.fail, hetvar = NULL, robust = "mean", logDose = NULL,
fctList = NULL, control = drmc(), lowerl = NULL, upperl = NULL)Arguments
formula
a symbolic description of the model to be fit. Either of the form 'response $~$ dose'
or as a data frame with response value in first column and dose in second column.
curve
a numeric vector or factor containing the grouping of the data.
pmodels
a data frame with a many columns as there are parameters in the non-linear function.
Or a list containing a formula for each parameter in the non-linear function.
weights
a numeric vector containing weights.
data
an optional data frame containing the variables in the model.
subset
an optional vector specifying a subset of observations to be used in the fitting process.
fct
a list with three or 5 elements specifying the non-linear
function, the accompanying self starter function, the names of the parameter in the non-linear f
unction and, optionally, the first and second derivatives.
adjust
a character string specifying the type of adjustment for variance inhomogeneity.
bc
a numeric value specifying the lambda parameter to be used in the Box-Cox transformation.
bcAdd
a numeric value specifying the constant to be added on both sides prior to Box-Cox transformation.
The default is 0.
type
a character string specifying the data type: continuous is the only option currently.
start
an optional numeric vector containing start values for all parameters in the model.
Overrules any self starter function.
na.action
a function which indicates what should happen when the data contain 'NA's. The default is 'na.fail'. To omit 'NA's use
'na.omit'.
hetvar
a vector specifying the grouping for heterogeneous variances.
robust
a character string specifying the rho function for robust estimation. Default is non-robust
least squares estimation ("mean"). Available robust methods are: median estimation ("median"),
least median of squares ("lms"), least trimmed squares ("lts
logDose
a numeric value or NULL. If log doses value are provided the base of the logarithm should be specified (exp(1) for the natural logarithm
and 10 for 10-logarithm).
fctList
a list of functions in case different functions need to be fit to different curves.
control
a list of arguments controlling constrained optimisation (zero as boundary), maximum number of iteration in the optimisation,
relative tolerance in the optimisation, warnings issued during the optimisation.
lowerl
~~Describe method here~~
upperl
~~Describe method here~~