nntsestimation {CircNNTSR} | R Documentation |
Computes the maximum likelihood estimates of the NNTS parameters
nntsestimation(M = 0, data, maxit = 500)
M |
Number of components in the NNTS |
data |
a vector of angles in radians |
maxit |
maximum number of iterations of the optimization algorithm |
coef |
vector of real numbers of dimension 2*M. The first M numbers are the SQUARED moduli of the c parameters, the sum must be less than 1/(2*pi). The last M numbers are the arguments of the c parameters |
loglik |
Optimum loglikelihood value |
AIC |
Value of Akaike's Information Criterion |
BIC |
Value of Bayesian Information Criterion |
convergence |
An integer code: 0 indicates successful convergence; error codes are: 1 indicates that the iteration limit maxit has been reached, 10 indicates degeneracy of the Nelder-Mead simplex |
For the maximization of the loglikelihood function the function constrOptim from the package stats is used
Juan Jose Fernandez-Duran y Maria Mercedes Gregorio-Dominguez
Fernandez-Duran. J.J. (2004). Circular Distributions Based on Nonnegative Trigonometric Sums, Biometrics, 60(2), 499-503.
a<-c(runif(10,3*pi/2,2*pi-0.00000000000001),runif(10,pi/2,pi-0.00000000000001)) est<-nntsestimation(2,a) nntsplot(est$coef,2)