Multivariate normal likelihood

Generates a 3 dimensional multivariate normal likelihood function.

generateTestDensityMultiNormal(mean = c(0, 0, 0),
  sigma = "strongcorrelation", sample = F, n = 1, throwErrors = -1)

Arguments

mean	vector with the three mean values of the distribution
sigma	either a correlation matrix, or "strongcorrelation", or "no correlation"
sample	should the function create samples
n	number of samples to create
throwErrors	parameter for test purpose. Between 0 and 1 for proportion of errors

Details

3-d multivariate normal density function with mean 2,4,0 and either strong correlation (default), or no correlation.

See also

testDensityBanana testLinearModel

Examples

# sampling from the test function
x = generateTestDensityMultiNormal(sample  = TRUE, n = 1000)(1000)
correlationPlot(x)
marginalPlot(x)
#> Warning: Parameter 'mat' is not of class 'bayesianOutput', set plotPrior to FALSE.

# generating the the density
density = generateTestDensityMultiNormal(sample  = FALSE)
density(x[1,])
#> [1] 0.2472597