Exercise

# Calculating the density of multivariate normal

For many statistical tasks, like hypothesis testing, clustering, and likelihood calculation, you are required to calculate the density of a specified multivariate normal distribution. In this exercise, you will use the `dmvnorm()`

function to calculate multivariate normal densities with specified mean and variance-covariance matrix at each of the observations from your previously generated sample `multnorm.sample`

.

The mean and the variance-covariance matrix are preloaded for you as objects `mu.sim`

and `sigma.sim`

.

Instructions

**100 XP**

- Use
`dmvnorm()`

to calculate the density heights of the 100 samples in`multnorm.sample`

for a bivariate normal. - Use
`scatterplot3d()`

to plot a 3D scatterplot of the density heights at each of the generated sample points.