numericDerivR: numericDerivR: numerically evaluates the gradient of an...

In nlsr: Functions for Nonlinear Least Squares Solutions - Updated 2022

numericDerivR: numerically evaluates the gradient of an expression. All in R

Description

This version is all in R to replace the C version in package stats

Usage

numericDerivR(
  expr,
  theta,
  rho = parent.frame(),
  dir = 1,
  eps = .Machine$double.eps^(1/if (central) 3 else 2),
  central = FALSE
)

Arguments

expr	expression or call to be differentiated. Should evaluate to a numeric vector.
theta	character vector of names of numeric variables used in expr.
rho	environment containing all the variables needed to evaluate expr.
dir	numeric vector of directions, typically with values in -1, 1 to use for the finite differences; will be recycled to the length of theta.
eps	a positive number, to be used as unit step size hh for the approximate numerical derivative (f(x+h)-f(x))/h (f(x+h)-f(x))/h or the central version, see central.
central	logical indicating if central divided differences should be computed, i.e., (f(x+h) - f(x-h)) / 2h (f(x+h)-f(x-h))/2h. These are typically more accurate but need more evaluations of f()f().

Value

The value of eval(expr, envir = rho) plus a matrix attribute "gradient". The columns of this matrix are the derivatives of the value with respect to the variables listed in theta.

Examples

ex <- expression(a/(1+b*exp(-tt*c)) - weed)
weed <- c(5.308, 7.24, 9.638, 12.866, 17.069, 23.192, 31.443,
              38.558, 50.156, 62.948, 75.995, 91.972)
tt <- 1:12
a <- 200; b <- 50; c <- 0.3
dhobb <- numericDerivR(ex, theta=c("a", "b", "c"))
print(dhobb)
# exf <- ~ a/(1+b*exp(-tt*c)) - weed
# Note that a formula doesn't work
# dh1 <-  try(numericDerivR(exf, theta=c("a", "b", "c")))

nlsr documentation built on Sept. 8, 2023, 5:48 p.m.