rand.norm {clusterv}R Documentation

Random generation of normal distributed data

Description

Random generation of a matrix of n columns with with diagonal covariance matrix (rand.norm.generate) or with full covariance matrix (rand.norm.generate.full). These functions are used by generate.sampleN functions 0 \leq N \leq 5 to generate the data.

Usage

rand.norm.generate(n = 5, mean = 0, sd = 1)
rand.norm.generate.full(n = 5, mean = c(0, 0), 
                        Sigma = matrix(c(0.1, 0, 0, 0.1), 2, 2))

Arguments

n

number of samples to be generated

mean

vector of means

sd

vector of standard deviations

Sigma

Covariance matrix

Value

a matrix of n columns with length(mean) rows. With rand.norm.generate Row[i] has mean mean[i] and standard deviation sd[i]. With rand.norm.generate.full Row[i] has mean mean[i]

Author(s)

Giorgio Valentini valentini@di.unimi.it

See Also

generate.sample0, generate.sample1, generate.sample2

generate.sample3, generate.sample4, generate.sample5

Examples

library(MASS)
rand.norm.generate(n = 10)
rand.norm.generate(n = 10, mean = c(0,1,2), sd = c(1,1,5))
rand.norm.generate.full()
rand.norm.generate.full(n = 10, mean = c(0, 0, 2), 
                        Sigma = matrix(seq(1,1.8, by=0.1), 3, 3))

[Package clusterv version 1.1.1 Index]