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)))
dist
#> <distribution[1]>
#> [1] MVN[2]

mean(dist)
#>      [,1] [,2]
#> [1,]    1    2
variance(dist)
#>      [,1] [,2]
#> [1,]    4    3
support(dist)
#> <support_region[1]>
#> [1] R^2
generate(dist, 10)
#> [[1]]
#>             [,1]       [,2]
#>  [1,] -2.0954181  0.8213753
#>  [2,] -0.3513529  2.5290962
#>  [3,]  1.5437237 -0.3503611
#>  [4,]  2.9712961  1.1839147
#>  [5,]  0.3628415  1.6472928
#>  [6,] -0.3379985  0.6611139
#>  [7,]  2.4679883  0.9856510
#>  [8,]  2.2635566  2.7749326
#>  [9,]  1.0962786  0.8520259
#> [10,]  1.2208742  3.1542455
#> 

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

cdf(dist, 4)
#> [1] 0.03217391

quantile(dist, 0.7)
#>          [,1]     [,2]
#> [1,] 2.048801 2.908288