nlmixrGradFun: Create a gradient function based on gill numerical...

In nlmixr: Nonlinear Mixed Effects Models in Population PK/PD

Create a gradient function based on gill numerical differences

Description

Create a gradient function based on gill numerical differences

Usage

nlmixrEval_(theta, md5)

nlmixrUnscaled_(theta, md5)

nlmixrGrad_(theta, md5)

nlmixrParHist_(md5)

nlmixrGradFun(
  what,
  envir = parent.frame(),
  which,
  thetaNames,
  gillRtol = sqrt(.Machine$double.eps),
  gillK = 10L,
  gillStep = 2,
  gillFtol = 0,
  useColor = crayon::has_color(),
  printNcol = floor((getOption("width") - 23)/12),
  print = 1
)

Arguments

theta	for the internal functions theta is the parameter values
md5	the md5 identifier for the internal gradient function information.
what	either a function or a non-empty character string naming the function to be called.
envir	an environment within which to evaluate the call. This will be most useful if what is a character string and the arguments are symbols or quoted expressions.
which	Which parameters to calculate the forward difference and optimal forward difference interval
thetaNames	Names for the theta parameters
gillRtol	The relative tolerance used for Gill 1983 determination of optimal step size.
gillK	The total number of possible steps to determine the optimal forward/central difference step size per parameter (by the Gill 1983 method). If 0, no optimal step size is determined. Otherwise this is the optimal step size determined.
gillStep	When looking for the optimal forward difference step size, this is This is the step size to increase the initial estimate by. So each iteration the new step size = (prior step size)*gillStep
gillFtol	The gillFtol is the gradient error tolerance that is acceptable before issuing a warning/error about the gradient estimates.
useColor	Boolean indicating if focei can use ASCII color codes
printNcol	Number of columns to printout before wrapping parameter estimates/gradient
print	Integer representing when the outer step is printed. When this is 0 or do not print the iterations. 1 is print every function evaluation (default), 5 is print every 5 evaluations.

Value

A list with 'eval', 'grad', 'hist' and 'unscaled' functions. This is an internal module used with dynmodel

Examples

func0 <- function(x){ sum(sin(x))  }

## This will printout every interation or when print=X
gf <- nlmixrGradFun(func0)

## x
x <- (0:10)*2*pi/10;
gf$eval(x)
gf$grad(x)

## x2
x2 <- x+0.1
gf$eval(x2)
gf$grad(x2)

## Gives the parameter history as a data frame
gf$hist()

nlmixr documentation built on March 27, 2022, 5:05 p.m.