Robert B. Gramacy Professor of Statistics

Response Surface Methods and Computer Experiments

STAT 6984 is a graduate "topics" statistics course at the interface between mathematical modeling via computer simulation, computer model meta-modeling (i.e., emulation/surrogate modeling), calibration of computer models to data from field experiments, and model-based sequential design and optimization under uncertainty. The treatment will include some of the historical methodology in the literature, and canonical examples, but will concentrate on modern statistical methods, computation and implementation in R, as motivated by modern application/data type and size.


  • Your final project is posted. It is due 13 Dec, 5pm. A leaderboard is available so you can check your progress relative to your peers.
  • The first class is Tuesday, 23 August, 12:30-1:45pm in RAND 320.
  • Classes are canceled the week of Sept 12 (i.e., 13th and 15th).


Homework Due at the start of lecture


The recommended language for this course is R, which can be obtained from CRAN. Other languages such as MATLAB are allowed but are not recommended. Examples in lecture, and help in office hours, etc., will be exclusively in R. Below are some helpful R resources: