Classification of urn models with multiple drawings

Markus Kuba

Published 2016-12-13Version 1

We consider multicolor urn models with multiple drawings. An urn model is called linear if the conditional expected value of the urn composition at time $n$ is a linear function of the composition at time $n-1$. For four different sampling schemes - ordered and unordered samples with or without replacement - we classify urns into linear and non-linear models. We also discuss representations of the expected value and the covariance for linear models.