PřF:MD116 Robust and non-param. meth. II - Course Information
MD116 Robust and non-parametric methods II
Faculty of ScienceSpring 2008
- Extent and Intensity
- 2/0. 2 credit(s) (plus 2 credits for an exam). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Jana Jurečková, DrSc. (lecturer)
- Guaranteed by
- prof. RNDr. Jana Jurečková, DrSc.
Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Fri 12:00–15:50 07011
- Prerequisites
- Mathematical statistics, teory of probability, linear models
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Mathematics - Economics (programme PřF, N-AM)
- Probability, Statistics and Mathematical Modelling (programme PřF, D-MA4)
- Statistics and Data Analysis (programme PřF, N-AM)
- Course objectives
- Robust statistical methods should work well not only under a specified distribution, but also in its neighborhood. We shall mainly concentrate on robust statistical estimation in the location and linear regression model, eventually in the multivariate statistical model.
- Syllabus
- (1) Basic concepts of robustness: Statistical functional, its continuity and derivatives on the metric space of probability distribution: Gateaux, Frechet and Hadamard derivatives. Influence function of the statistical functional and numerical characteristics of robustness based on the influence function: global and local robustness. Other characteristics of robustness: breakdown point, maxbias, tail behavior of the statistical functional. (2) Robust estimators of a scalar parameter, especially of the location parameter: and mutual relations. One-step versions of robust estimators. (3) Robust estimation in the linear regression model under random and nonrandom designs. M-, L-, R-estimators of the regression parameter vector, their influence functions and other properties. Regression quantiles and their applications. (3) Some goodness-of-fit tests in the presence of nuisance parameters of regression and scale. Extension of the Shapiro-Wilk test of normality.
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period.
The course is taught only once.
General note: Na podzim 2006 bude kurz zaměřen na odhady parametrů konečných populací a teorii statistického výběru.
- Enrolment Statistics (Spring 2008, recent)
- Permalink: https://is.muni.cz/course/sci/spring2008/MD116