Links
Background on Lectures 1 and 2 (Course Introduction and Quick Review):
Capture/recapture models:
Poisson distribution:
"Let's Make a Deal" game show:
Additional background on the "Let's Make a Deal" controversy:
"Let's Make a Deal" applet:
Hazard functions (with an application to cricket):
Method of maximum likelihood:
Method of moments:
The Law and Bayes's Rule
Random Number Generators
- http://www.wam.umd.edu/~petersd/660/rando.html
- http://www.iro.umontreal.ca/~simardr/random.html#Rand
For the history of the Monte Carlo method, please see:
Computing pi via Monte Carlo:
The Law of Large Numbers (LLN):
A LLN applet:
The Central Limit Theorem (CLT):
- http://en.wikipedia.org/wiki/Central_limit_theorem
- http://www.vias.org/simulations/simusoft_cenlimit.html
- http://www.statisticalengineering.com/central_limit_theorem.htm
The Delta Method:
The Bootstrap:
Variance Reduction:
Least squares:
Bio on Gauss:
Weighted least squares:
Recursive least squares:
Autoregressive moving average (ARMA) models:
Kalman filter:
Kalman filter learning tool:
Application of the Kalman filter to GPS:
History of the Kalman filter (and its applications):
Bio of Kalman:
Background on Markov Chains and Stochastic Control
Markov chains:
Use of Markov chain ideas in Google's page-rank algorithm:
Discussion of Markov chain Monte Carlo (with an emphasis on applications in computer vision):
Stochastic control/Markov decision processes:
Optimal stopping:
Biography of A.A. Markov: