Computational statistics, spring 2009 (Laskennallinen tilastotiede)

Last modified by ppkoisti@helsinki_fi on 2024/03/27 09:59

Computational statistics, spring 2009 (Laskennallinen tilastotiede)

Lecturer

Petri Koistinen

Scope

8 cu.

Type

Advanced studies

Lectures

Weeks 3-9 and 11-18 Mon 12-14, Fri 12-14 B120.

The lectures will be given in English. Luennot pidetään englanniksi.

No lecture on Mon 16 Feb.

Easter holiday 9.-15.4.

Course exams

First course exam will be held Fri 27 Feb at 14-16 in room B120.

Second course exam will be held Mon 27 Apr at 12-14 in room B120.

Prerequisites

  • Basic skills in (multivariate) differential and integral calculus (partial derivatives and multiple integrals).
  • Basic skills in probability and linear algebra (calculations involving multivariate distributions, e.g., Todennäköisyyslaskennan kurssi).
  • Some previous exposure to Bayesian inference would be helpful.

Description

This course gives an overview of computational methods which are useful especially in Bayesian statistics. Topics include

  • Review of probability and Bayesian inference.
  • Methods for generating independent samples from distributions.
  • Classical Monte Carlo integration and importance sampling.
  • Approximating the posterior using numerical quadrature or Laplace expansion.
  • EM algorithm.
  • MCMC methods: Gibbs and Metropolis-Hastings sampling.
  • Auxiliary variable methods in MCMC.

Bibliography

Lecture notes.

Requirements

To pass the course you should

  • pass the exam (either two course exams at the end of the periods or a single final exam)
  • pass the compulsory practical work (harjoitustyö)
  • grading is based on the exam and exercise activity
  • laskuharjoitustehtävien ratkaisut voi esittää suomeksi; harjoitustyön voi tehdä suomeksi; tentissä voi vastata suomeksi.

Status

  • This is a compulsory course in the EuroBayes master's degree program in Bayesian statistics and decision analysis.
  • Tällä kurssilla voidaan korvata kurssi Tilastollinen laskenta, joka esiintyy opinto-oppaassa, mutta jonka nimistä kurssia ei luennoida. Kurssi soveltuu esim. tilastotieteen koulutusohjelman valinnaiseksi erikoiskurssiksi joko kandidaatin tai maisterin tutkintoon.
  • This is also a suitable course for the MBI master's degree program in bioinformatics.

More information

This course will be similar to the course given fall 2007 with the title

Computational Methods in Statistics.

Registration at the first lecture

Exercise groups

Group

Day

Time

Place

1.

Fri

14-16

B120

First exercise session on Jan 23.