Statistical Modeling with Stochastic Processes Winter 2011 Part 2 : Basics of Dirichlet processes

@inproceedings{Scribe2011StatisticalMW,
  title={Statistical Modeling with Stochastic Processes Winter 2011 Part 2 : Basics of Dirichlet processes},
  author={Alexandre Bouchard-C{\^o}t{\'e} Scribe},
  year={2011}
}
  • Alexandre Bouchard-Côté Scribe
  • Published 2011
To motivate the Dirichlet process, let us consider a simple density estimation problem: modeling the height of UBC students. We are going to take a Bayesian approach to this problem, considering the parameters as random variables. In one of the most basic models, one would define a mean and variance random parameter θ = (μ, σ), and a height random variable normally distributed conditionally on θ, with parameters θ. Using a single normal distribution is clearly a defective approach, since for… CONTINUE READING