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]