NR | R Documentation |
Solves an equation equation of form f(x)=0, for scalar x using the Newton-Raphson algorithm.
NR(init, fn, gr, crit = 6, range = c(-Inf, Inf))
init |
Numeric scalar, The initial guess for x. |
fn |
An R-function returning the scalar value of f(x), with x as the only argument. |
gr |
An R-function returning the first derivative of f(x), with x as the only argument. |
crit |
Convergence criteria. The upper limit for the absolute value of f(x) at an accepted the solution. |
range |
A two-unit vector giving the upper and lower bounds for x. The solution is searched from within this range. |
The function is a straightforward implementation of the well-known Newton-Raphson algorithm.
A list of components
par |
the value of x in the solution |
crit |
the value of f(x) at the solution |
If estimation fails (no solution is found during 100000 iterations), both e lements of the solution are NA's.
Lauri Mehtatalo <lauri.mehtatalo@uef.fi>
See NRnum
for a vector-valued x without analytical gradients.
## Numerically solve Weibull shape for a stand ## where DGM=15cm, G=15m^2/ha and N=1000 trees per ha func<-function(shape,G,N,DGM) { ## print(G,DGM,N) val<-pi/(4*gamma(1-2/shape)*log(2)^(2/shape))-G/(N*DGM^2) val } grad<-function(shape) { pi/4*(-1)* (gamma(1-2/shape)*log(2)^(2/shape))^(-2)* (gamma(1-2/shape)*digamma(1-2/shape)*2*shape^(-2)*log(2)^(2/shape)+ log(2)^(2/shape)*log(log(2))*(-2)*shape^(-2)*gamma(1-2/shape)) } shape<-NR(5,fn=function(x) func(x,G=10000*15,1000,15),gr=grad,crit=10,range=c(2.1,Inf))$par
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