# mnntsloglik: MNNTS log-likelihood function In CircNNTSR: Statistical Analysis of Circular Data using Nonnegative Trigonometric Sums (NNTS) Models

## Description

Computes the log-likelihood function with MNNTS density for data

## Usage

 `1` ```mnntsloglik(data, cpars = 1/sqrt(2 * pi), M = 0, R = 1) ```

## Arguments

 `data` Matrix of angles in radians, a column for each dimension, a row for each data point. `cpars` Parameters of the model. A vector of complex numbers of dimension prod(M+1). The first element is a real and positive number. The first M+1 elements correspond to dimension one, next M+1 elements correspond to dimension two, and so on. The sum of the SQUARED moduli of the c parameters must be equal to 1/(2*pi). `M` Vector of length R with number of components in the MNNTS for each dimension. `R` Number of dimensions.

## Value

The function returns the value of the log-likelihood function for the data.

## Author(s)

Juan Jose Fernandez-Duran and Maria Mercedes Gregorio-Dominguez

## References

Fernandez-Duran, J.J. and Gregorio-Dominguez, M.M. (2009) Multivariate Angular Distributions Based on Multiple Nonnegative Trigonometric Sums, Working Paper, Statistics Department, ITAM, DE-C09.1

## Examples

 ```1 2 3 4 5 6 7 8``` ```M<-c(2,3) R<-length(M) data<-c(0,pi,pi/2,pi,pi,3*pi/2,pi,2*pi,2*pi,pi) data<-matrix(data,ncol=2,byrow=TRUE) data ccoef<-mnntsrandominitial(M,R) mnntsdensity(data,ccoef,M,R) mnntsloglik(data,ccoef,M,R) ```

CircNNTSR documentation built on Feb. 18, 2020, 9:15 a.m.