Where are we and what should I be doing?
April 21, 2026
We finished the prior sensitivity with importance sampling and SIR example.
Next is Bayes for mu | sigma and sigma | mu and then Gibbs sampling.
April 16, 2026
Finished Monte Carlo notes.
Almost finished example R code on prior sensitivity.
Next topic: Markov Chain Monte Carlo.
April 9, 2026
We finished the basic rejection sampling notes and
we are about to start "Intuition for Rejection Sampling", slide 20 in the monte carlo notes.
We also looked at the example script for drawing truncated normals but did
not quite finish it.
No more homework, but I hope you have started your project!!
April 4, 2026
Final project is due May 6.
April 1, 2026
There are no classes (no zoom, no in-person) April 2.
I am hoping to be able to zoom April 7 (next Tuesday).
I have put recordings of lectures for the rest of the EM notes
on the webpage in the EM section.
see:
Recordings:
The General EM algorithm and mixtures of multivariate normals
More on the EM algorithm
The EM algorithm and missing values
Next zoom class we will start on the section "Intro to Bayes ..."
and then quickly go to "Monte Carlo".
See the suggested project "EM algorithm for a mixture of normals" on the webpage.
This just says code up the EM algorithm for mixtures of normals and play around with it.
So, the suggest projects are:
- Gaussian processes
- single layer neural networks
- Mixtures of normals with EM
Sounds good to me !!!.
BUT REMEMBER, YOU CAN DO WHATEVER YOU LIKE AND YOU CAN DO THE PROJECT IN GROUPS
So that you can focus on the project there will not be any more homework.
March 24, 2026
About to do general EM algorithm, Section 5 in the EM notes (slide 40).
March 19, 2026
We are about to do slide 18 on "Clustering" in the EM notes.
Homework 3 is on the webpage, due April 3 (we can negotiate.).
March 5, 2026
We are about to do Gradient Descent in the optimization notes.
Homework 2 is due March 16.
February 26, 2026
Just finished the multivariate normal mle.
Homework 2 is due March 16.
February 12, 2026
We stopped at ''Statistical Connectons'' in the linear algebra review notes.
February 10, 2026
We just did slide 40 of linear algebra,
about to do ''Sum of Subspaces''.
February 5, 2026
We finished looking at calling C++ from R and python.
Nex time we will start the next section of notes: Matrix Decompositions in Statistics.
Homework 1 is due February 11.
Homework can be done in groups.
Rob office hours, Monday zoom at 7pm.
January 29, 2026
We looked at writing the mll (minus log likelihood) for the logit in C++
and calling it out of R using Rcpp and R CMD SHLIB.
Next time we meet we will look calling C out python using cython
and using Rstudio to write and R package which call C++ using Rcpp.
Homework 1 is on the webpage and due February 11.
NO CLASS February 3, I'm tied up with medical issues.
January 27, 2026
We finished the R and python scripts on speeding up the computations
of the logit likelihood by choosing data structures and vectorization.
Next class we will look at doing the computation directly in C/C++ and
calling C out of R and python.
January 22, 2026
We are working the R code to compute the likelihood for the logit model.
We just compared the AIC value we got from our likelihood computation to the value
from the R logistic regression output.
We also jumped ahead to the mixture notes to get a quick overview of deviance, AIC, and BIC.
Next time we will finish the R in which we compare speeds with different data structures
and with and without vectorization. We will also look at the C++ versions.
January 20, 2026
Last class we quickly breezed throught the R and python Hello worlds.
Next class we will look at at vectorization with the logit likelihood as an example.
January 15, 2026
Last class we went over the syllabus and course organization.
We ended up going through the python information webpage.
Next class let's quickly look at the colab example in the
python information and then the Hello world in python.
The we will look at the R material.
After that, we start the actual course by looking at
vectorization, data structures, and using C++ when computing
the logit likelihood.
If you have a mac, you might want to make sure you have the Xcode installed
so you can try the clang C++ compiler.
January 13, 2026
Folks,
I have had some health issues so the first class (January 13) is cancelled.
I'm hoping to zoom on Thursday January 15 and then make it in person the following week (January 20,22).
Note that the in-person classes will also be available via zoom and recordings of all classes will be available.
All class materials are available at:
https://www.rob-mcculloch.org/2026_cs/webpage/index.html
Please check out the webpage. In particular note the link
Where are we and what I should be doing?
https://www.rob-mcculloch.org/2026_cs/webpage/ww.html
Basic computational skills are needed for the class.
I will support R and python, but you can use other software (e.g. matlib) if you want.
For python please check out my notes at:
https://www.rob-mcculloch.org/python/index.html.
If you don't have a python/data science installed on your machine you
might want to try installing anaconda as discussed on the webpage.
Please also have a look at
https://www.rob-mcculloch.org/python/Py_Hello-World_Regression.html (at bottom of the webpage above).
This is my basic intro to data science/scikit-learn.
If you don't know python, I think it is feasible to learn it as we go along
but note my suggested books at:
https://www.rob-mcculloch.org/books.txt.
For R please check out my notes at:
https://www.rob-mcculloch.org/R/index.html.
If you don't have a R/rstudio installed on your machine you should do so.
Also have a look at https://www.rob-mcculloch.org/R/R_Hello-World_Regression.html.
This is my basic introduction to R.
If you don't know R, I think it is feasible to learn it as we go along
but note my suggested books at:
https://www.rob-mcculloch.org/books.txt.
January 12, 2026
Zoom meetings:
Hi there,
Robert McCulloch is inviting you to a scheduled Zoom meeting.
Topic: STP 540 Computational Statistics
Time: Jan 13, 2026 12:00 PM Arizona
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January 1, 2026
Nothing to be done at this time.