dr4plEst: Private function to fit the 4PL model to dose-response data

Description Usage Arguments Value

View source: R/main.R

Description

Private function that actually fits the 4PL model to data. If the Hill bounds are attained at the end of optimization processes, then an indicator of convergence failure so that dr4pl.default can look for a remedy for convergence failure.

Usage

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dr4plEst(
  dose,
  response,
  init.parm,
  trend,
  method.init,
  method.optim,
  method.robust,
  use.Hessian,
  level,
  upperl,
  lowerl,
  ...
)

Arguments

dose

Vector of dose levels

response

Vector of responses

init.parm

Vector of initial parameters of the 4PL model supplied by a user.

trend

Indicator of whether a dose-response curve is a decreasing θ[3]<0 or increasing curve θ[3]>0. The default is "auto" which indicates that the trend of the curve is automatically determined by data. The option "decreasing" will impose a restriction θ[3]<=0 while the option "increasing" will impose a restriction θ[3]>=0 in an optimization process.

method.init

Method of obtaining initial values of the parameters. Should be one of "logistic" for the logistic method or "Mead" for the Mead method. The default option is the Mead method.

method.optim

Method of optimization of the parameters. This argument is directly delivered to the constrOptim function provided in the "base" package of R.

method.robust

Parameter to select loss function for the robust estimation method to be used to fit a model. The argument NULL indicates the sum of squares loss, "absolute" indicates the absolute deviation loss, "Huber" indicates Huber's loss and "Tukey" indicates Tukey's biweight loss.

use.Hessian

Indicator of whether the Hessian matrix (TRUE) or the gradient vector is used in the Hill bounds.

level

Confidence level to be used in Hill bounds computation.

upperl

upper limit to init.parm

lowerl

lower limit to init.parm

...

Further arguments to be passed to constrOptim.

Value

List of final parameter estimates, name of robust estimation, loss value and so on.


dr4pl documentation built on Aug. 17, 2021, 5:06 p.m.