Course Descriptions

The Course Descriptions catalog describes all undergraduate and graduate courses offered by Michigan State University. The searches below only return course versions Fall 2000 and forward. Please refer to the Archived Course Descriptions for additional information.

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STT 961  Convergence of Measures and Stochastic Processes

Description:
Convergence of measures on metric spaces. Prohorov's theorem. Function spaces with the uniform and Skorohod metric. Empirical processes. Applications.
Effective Dates:
FS95 - SS05


STT 961  Convergence of Measures and Stochastic Processes

Semester:
Fall of even years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 882
Description:
Convergence of measures on metric spaces. Prohorov's theorem. Function spaces with the uniform and Skorokhod metric. Empirical processes. Weak convergence of Martingales. Applications.
Effective Dates:
US05 - US07


STT 961  Convergence of Measures and Stochastic Processes

Semester:
Fall of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 882
Description:
Convergence of measures on metric spaces. Prohorov's theorem. Function spaces with the uniform and Skorokhod metric. Empirical processes. Weak convergence of Martingales. Applications.
Effective Dates:
FS07 - US08


STT 961  Convergence of Measures and Stochastic Processes

Semester:
Spring of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Recommended Background:
STT 882
Description:
Convergence of measures on metric spaces. Prohorov's theorem. Function spaces with the uniform and Skorokhod metric. Empirical processes. Weak convergence of Martingales. Applications.
Effective Dates:
FS08 - US13


STT 961  Weak Convergence and Asymptotic Theory

Semester:
Fall of odd years
Credits:
Total Credits: 3   Lecture/Recitation/Discussion Hours: 3
Prerequisite:
STT 872 and STT 882
Restrictions:
Open to doctoral students in the Statistics major or approval of department.
Description:
Maximal inequalities, covering numbers, symmetrization technique, Glivenko-Cantelli Theorems, Donsker Theorems and some results for Gaussian processes, Vapnik-Chervonenkis classes of sets and functions, applications to M-estimators, bootstrap, delta-method
Effective Dates:
FS13 - Open