How do I calculate the inverse of the cumulative distribution function (CDF) of a multivariate normal distribution? Does it even exist for the multivariate case?
I know this is possible for a univariate case in python as
from scipy.stats import norm norm.ppf(0.95, loc=10, scale=2) # mean=10,variance=2, probability=0.95 Out: 0.94999999999999996 # x value corresponding to given probability
Can somebody tell me a function similar to this for a multivariate case in Python or R?
Sample Input : mean is a dimensional vector variance is p*p matrix probability(between 0 &1) Expected output : 'x' which would be a p dimensional vector