The multivariate normal distribution

dist_multivariate_normal(mu = 0, sigma = diag(1))

Arguments

mu

A list of numeric vectors for the distribution's mean.

sigma

A list of matrices for the distribution's variance-covariance matrix.

See also

mvtnorm::dmvnorm, mvtnorm::qmvnorm

Examples

dist <- dist_multivariate_normal(mu = list(c(1,2)), sigma = list(matrix(c(4,2,2,3), ncol=2)))
dimnames(dist) <- c("x", "y")
dist
#> <distribution[1]>
#> [1] MVN[2]

mean(dist)
#>      x y
#> [1,] 1 2
variance(dist)
#>      x y
#> [1,] 4 3
support(dist)
#> <support_region[1]>
#> [1] R^2
generate(dist, 10)
#> [[1]]
#>                 x          y
#>  [1,]  2.41166586  4.7343095
#>  [2,]  2.05624208  2.2215200
#>  [3,]  0.86251835  2.3519657
#>  [4,]  1.68848502  1.3478514
#>  [5,]  2.41133076  1.3724569
#>  [6,] -1.03574719  2.4842942
#>  [7,]  0.04990478  1.3453962
#>  [8,]  0.97289793  3.7787571
#>  [9,]  0.78530930  3.6150883
#> [10,]  0.59753978 -0.1314307
#> 

density(dist, cbind(2, 1))
#> [1] 0.02829422
density(dist, cbind(2, 1), log = TRUE)
#> [1] -3.565098

cdf(dist, 4)
#> [1] 0.8412602

quantile(dist, 0.7)
#>             x        y
#> [1,] 2.048801 2.908288
quantile(dist, 0.7, type = "marginal")
#>             x        y
#> [1,] 2.048801 2.908288