# vmnb.pred: Prediction with some naive Bayes classifiers for circular... In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

 Prediction with some naive Bayes classifiers for circular data R Documentation

## Prediction with some naive Bayes classifiers for circular data

### Description

Prediction with some naive Bayes classifiers for circular data.

### Usage

``````vmnb.pred(xnew, mu, kappa, ni)
spmlnb.pred(xnew, mu1, mu2, ni)
``````

### Arguments

 `xnew` A numerical matrix with new predictor variables whose group is to be predicted. Each column refers to an angular variable. `mu` A matrix with the mean vectors expressed in radians. `mu1` A matrix with the first set of mean vectors. `mu2` A matrix with the second set of mean vectors. `kappa` A matrix with the kappa parameters for the vonMises distribution or with the norm of the mean vectors for the circular angular Gaussian distribution. `ni` The sample size of each group in the dataset.

### Details

Each column is supposed to contain angular measurements. Thus, for each column a von Mises distribution or an circular angular Gaussian distribution is fitted. The product of the densities is the joint multivariate distribution.

### Value

A numerical vector with 1, 2, ... denoting the predicted group.

### Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

` vm.nb, weibullnb.pred, nb.cv `

### Examples

``````x <- matrix( runif( 100, 0, 1 ), ncol = 2 )
ina <- rbinom(50, 1, 0.5) + 1
a <- vm.nb(x, x, ina)
a2 <- vmnb.pred(x, a\$mu, a\$kappa, a\$ni)
``````

Rfast2 documentation built on May 29, 2024, 8:45 a.m.