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.

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,] -3.60009185 0.5562756
#>  [2,] -0.05923307 1.2763818
#>  [3,]  1.98769657 1.9861989
#>  [4,]  1.51301349 2.3132829
#>  [5,]  2.41166586 4.7343095
#>  [6,]  2.05624208 2.2215200
#>  [7,]  0.86251835 2.3519657
#>  [8,]  1.68848502 1.3478514
#>  [9,]  2.41133076 1.3724569
#> [10,] -1.03574719 2.4842942
#>

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