STATISTICS 4CI3/6CI3

Computational Methods For Inference

Winter Term 2019


Instructor : Angelo J. Canty
Office :HH 209
Phone:(905) 525-9140 x 27079
Email: cantya@mcmaster.ca
Textbooks (not required): Introducing Monte Carlo Methodx with R by C. Robert and G. Casella, Springer, 2010
Bootstrap Methods and Their Application by A.C. Davison and D.V. Hinkley, Cambridge University Press, 1997.
Lectures: Monday 1:30 - 2:20 in HH 104
Wednesday 1:30 - 2:20 in HH 104
Thursday 1:30 - 2:20 in HH 104
Office Hours : Monday 2:30 - 3:30
Wednesday 2:30 - 3:30
Thursday 2:30 - 3:30
or at other times by e-mail appointment


Course Outline

Note: In order to read the course outline and many other documents on this page you need the Adobe Acrobat Reader. If you do not have this installed on your computer then it can be downloaded by clicking on the button below.


Notices

Important announcements and notices regarding the website and the course will be posted here.

April 12, 2019 I have posted the solution set including R code for the 4th assignment. I hope to have the assignments ready for collection during my office hours on Monday.

April 11, 2019 I will be available in my office at the following dates and times in April. I will generally not be available outside of these times other than by email. Also please note that I am also teaching a large undergraduate course so may need to restrict students to ~10 minutes at a time if there are a lot of students seeking help. Also note that I generally need to leave promptly at the of the posted office hours so please try to come earlier in the session to ensure you get your questions answered. I hope to have your final assignment ready for pickup during these office hours from Monday onwards.
DateTime
Friday April 1210am-12pm, 2pm-4pm
Monday April 1512pm-3pm
Wednesday April 171pm-4pm
Thursday April 1810am-3pm
Monday April 2210am-4pm
Tuesday April 231pm-3pm
Thursday April 2510am-3pm

April 11, 2019 I have posted the code I used last week for the smoothed and shrunk smoothed bootstrap as well as the bootstrap confidence intervals example.

March 29, 2018.The webste for course evaluations is now open. Please do contribute your views about what you liked and constructive criticism of what did not work for you so that I can continue to improve this course in future offerings. The details are here.

March 28, 2018. I have now posted the fourth (and final!) assignment for this course. It is due at the start of our final class on Monday April 8.

March 28, 2018. I have posted the parametric bootstrap code that we used in class yesterday as well as the code we were doing today. We did not finish the latter file today but will do so on Monday.

March 25, 2018. Sorry I neglected to post the new lecture notes before class today. They have now been posted. I have also posted the R code for the two examples of Monte Carlo Bayesian inference we did last week.

March 25, 2018. I have posted the solution set for the third assignment.

March 18, 2019 It has been pointed out that there are two errors in my definition of the bivariate normal density in Question 3 of Assignment 3 (a subscript missing on one of the variances and the square missing on the final term involving y alone). Sorry for these typos. I have now corrected them and reposted the assignment.

March 16, 2019 I have extended the due date for the thrid assignment until Thursday March 21 to give us more time to look at Monte Carlo Bayesian inference in class on Monday.

March 16, 2019 I have posted the code we used in class on Wednesday, March 13.

March 16, 2019 I have posted the solution set for the midtrm test.

March 8, 2019 Sorry, I neglected to post the R code for the examples of Markov chains that we looked at in class on February 25. I have done that now.

March 8, 2019 I have posted your third assignment which is due at the start of class on Monday March 18, 2019. There are no extra questions for STATS 6CI3 students on this assignment since your project proposal is due on the same week (Thursday March 21, 2019).

March 8, 2019 I have posted the sixth set of lecture notes.

March 6, 2019 The test tomorrow will take place in University Hall Room 213 and not the usual lecture room as is incorrectly stated in the course outline. Sorry for any confusion.

March 4, 2019 I have posted the solutions to the second assignment.

February 28, 2019 I have posted code for the Metropolis-Hastings examples done in class today and yesterday.

February 22, 2019 I have posted the fifth set of lecture notes.

February 14, 2019 I have now posted the second assignment.

February 13, 2019 I have posted the solutions and associated R code for the first assignment.

February 11, 2019 I have posted the fourth set of lecture notes.

February 4, 2019 I have posted the code used in class today. Also in the file is code for the Accept-Reject algorithm to generate Beta random variables. We started this last week and I meant to finish it today but forgot, sorry. Please review the code and I can answer any questions in class on Wednesday.

January 31, 2019 I got some of the math in the example incorrect today so here is the corrected version. I have posted the code used today as well as the code to generate from a finite mixture of normal distributions from yesterday also.

January 30, 2019 Based on student questions I have clarified some aspects of the first assignment and fixed a typographical error.

January 30, 2019 I have now posted the third set of lecture notes.

January 25, 2019 The first assignment has now been posted and is due at the START OF CLASS on Monday, February 4.

I have now posted the code that I used in class on Wednesday.

January 20, 2019 I have now posted the second set of lecture notes.

January 2, 2019 Happy new year and welcome to Stats 4CI3/6CI3 Computational Methods for Inference. The first class will take place in HH-104 at 1:30 on Monday, January 7. The course outline and the first set of lecture notes have now been posted. This course will use the statistical programming language R quite extensively and students are strongly encouraged to download their own copy of R. It is available free of charge from http://cran.r-project.org for Windows, Linux or Macintosh operating systems.

Lecture Notes

Copies of my lecture notes will be posted here. I will generally try to have the notes posted prior to their use in class.



R Code for Examples

I will post the R code for examples done in class here.


Assignments

Assignments will be posted here at least one week before they are due and their solutions will be posted approximately one week after the due date. Written assignments are due at the start of class on their due date, late assignments will not be accepted except in extreme circumstances. Your assignment must contain a printout of commented R code used. You should also send a plain text file with the commented R code used should also be sent to me at cantya@mcmaster.ca. The subject of the email must include the course number, the assignment number, your name and id. Failure to include and send your code will result in a significant loss of marks for the assignment. The dates given below are subject to change depending on our progress in the course. Any change will be posted here and announced in class.



Midterm Test





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This page is maintained by Angelo Canty, cantya@mcmaster.ca
Last updated on April 12, 2019