Solve a Systems of Nonlinear Equations Using the Newton's Method
Solves a system of equations of form f_1(x) = 0,f_2(x) = 0,...,f_p(x) = 0 for
vector x using the multidimensional version of the Newton-Raphson algorithm.
The gradients are solved numerically within the function using R-function numericDeriv.
NRnum(init, fnlist, crit = 6, ...)
init |
vector of initial values for x. |
fnlist |
list of R-functions for f_1(x), f_2(x), ..., f_p(x) each function gets a vector-valued argument x and returns a scalar value. |
crit |
Convergence criterion. Stop iteration when (|f_1(x)|+|f_2(x)|+...+|f_p(x)|<crit). |
... |
Other arguments passed to the functions of |
A list of components
par |
the value of vector x in the solution |
crit |
the value of the convergence criterion at the solution |
If estimation fails (no solution is found during 100 iterations), both elements of the solution are NA's.
Lauri Mehtatalo, <lauri.mehtatalo@uef.fi>
Function NR.
# Moment-based recovery of Weibull parameters mu<-14 mu2<-210 muf<-function(theta) theta[2]*gamma(1+1/theta[1])-mu mu2f<-function(theta) theta[2]^2*gamma(1+2/theta[1])-mu2 functions<-list(muf,mu2f) momrec<-NRnum(c(3,13),functions) momrec$par
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