MATH 281A Fall 2013
Department of Mathematics, University of California, San Diego
11:o8:13 Homework 5 has been posted here. Due in class on Thursday, November 14th, AP&M 5151.
1o:26:13 Additional Office Hours of Prof. B have changed to Friday (Nov, 1st) 2:00pm-4:00pm & Monday (Nov 4th) 2:00pm-4:00pm.
1o:26:13 Homework 4 has been posted here. Due in class on Tuesday, November 5th, AP&M 5151.
1o:26:13 Reading Assignment 4 = Sections 1,2,3 & 4 of Chapter 2/ Theory of Point Estimation.
1o:15:13 Office Hours of Prof. B have changed to Wednesday 2:30pm-4:30pm.
1o:12:13 Schedule of classes for the week of Oct 21st: Friday 25th, 4:30pm-5:50pm & Saturday 26th, 10:00am-11:30am
1o:11:13 Homework 2 has been posted here. Due on Friday, October 18th, 3pm AP&M 5151.
1o:11:13 Reading Assignment 2 = Sections 5 & 6 of Chapter 1/ Theory of Point Estimation.
1o:o2:13 Homework 1 has been posted here. Due on Friday, October 11th, 3pm AP&M 5151.
1o:o2:13 Reading Assignment 1 = Sections 1 & 2 of Chapter 1/ Theory of Point Estimation.
o9:26:13 Extension students, please send an email to the instructor to be added to the class email list.
o9:26:13 Read the whole page and the syllabus.
Fri Apr 12 12:09:57 PST 2013 | archive
12:o5:13 Rescheduled for Saturday November 23rd, 11:00am-12:30pm
12:o3:13 Rescheduled for Saturday November 16th, 11:00am-12:30pm
12:o2:13 Take home final distributed.
11:28:13 Minimax Estimation of the Mean of a Normal Distribution when the Parameter Space is Restricted.
11:26:13 More general Shrinkage Estimators.
11:23:13 Shrinkage Estimators in the normal case.
11:21:13 Least favorable priors. Simultaneous Estimation.
11:19:13 Midterm Exam .
11:16:13 Minimax Principles. Admissibility. Worst case risk bounds.
11:14:13 Examples on Bayes Estimation with single, hierarchical and empirical bayes principles.
11:12:13 Binary Classification, 0-1 loss and Bayes Risk
11:o7:13 Estimating quantiles, probabilities and densities. Examples of Bayes Estimators.
11:o5:13 Midterm Exam .
1o:31:13 Average Risk Optimality and Bayes Estimators.
1o:29:13 Information Inequality.
1o:26:13 Examples of UMVU estimators: admisable, inadmisable and non-existant.
1o:25:13 UMVU estimators: Rao-Blackwel theorem and Lehmann-Scheffe theorem.
1o:24:13 Rescheduled for Saturday 26th, 10:00am-11:30am
1o:22:13 Rescheduled for Friday 25th, 4:30pm-5:50pm
1o:17:13 Ancillary and Completeness of Statistics.
1o:15:13 Neyman Fisher Factorization Theorem. Minimal Sufficient Statistics.
1o:1o:13 Minimal Exponential Families and Sufficient Statistics
1o:o8:13 Exponential Families: Curved, Reduced or Full Rank
1o:o4:13 Measurability and Integration
1o:o2:13 Sigma algebra and Measurable Spaces
o9:26:13 Parametric Models and Optimality of Estimators
o9:26:13 Syllabus [pdf]
Lecture: Tu&Th 11:30-12:50pm, AP&M B412
Theory of Point Estimation, second edition, by Lehmann and Casella (required)
Asymptotic Statistics, by van der Vaart
Mathematical Statistics, Second Edition, Bickel and Doksum
Gaussian estimation: Sequence and wavelet models, Johnstone pdf>