I have a dataframe, with data of several continuous variables. The variables are not independent.
My goal is to sample from the distribution that generated this data.
What's a relatively easy and practical way to do this?
One quick and dirty approach I can think of is to discretize all variables and then sample from the buckets. Is this a decent approach? What's a better one?
A cleaner fix could be to do PCA and do the above approach on the principal components. However this is not ideal in my case due to user needs.