| deriva {marqLevAlg} | R Documentation |
Numerical derivatives
Description
The function computes the first derivates and the information score matrix. Central finite-differences and forward finite-differences are used for the first and second derivatives respectively.
Usage
deriva(nproc = 1, b, funcpa, .packages = NULL, ...)
Arguments
nproc |
number of processors for parallel computing |
b |
value of parameters to be optimized over |
funcpa |
function to be minimized (or maximized), with argument the vector of parameters over which minimization isto take place. It should return a scalar result. |
.packages |
character vector of packages that funcpa depends on |
... |
other arguments of the funcpa function |
Value
v |
vector containing the upper part of the information score matrix and the first derivatives |
rl |
the value of the funcpa function at point b |
Author(s)
Viviane Philipps, Boris Hejblum, Cecile Proust-Lima, Daniel Commenges
References
Donald W. Marquardt An algorithm for Least-Squares Estimation of Nonlinear Parameters. Journal of the Society for Industrial and Applied Mathematics, Vol. 11, No. 2. (Jun, 1963), pp. 431-441.
Examples
b <- 0.1
f <- function(b){return((2*b[1]**2+3*b[1]))}
d <- deriva(b=b,funcpa=f)