Subjects

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Generalised Linear Models - NSTP126

Title:	Zobecněné lineární modely
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2010
Semester:	summer
E-Credits:	6
Hours per week, examination:	summer s.:2/2, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	cancelled
Language:	Czech
Teaching methods:	full-time
Additional information:	http://www.karlin.mff.cuni.cz/~kulich/vyuka/glm/index.html

Guarantor:	doc. Mgr. Michal Kulich, Ph.D.
Class:	DS, pravděpodobnost a matematická statistika Mat. statistika
Classification:	Mathematics > Probability and Statistics
Co-requisite :	{NSTP002 nebo NSTP202}
Pre-requisite :	{NSTP094 nebo (NSTP194 a NSTP195)}, {NSTP001 nebo NSTP201}
Interchangeability :	{NSTP196 a NSTP197}
Incompatibility :	NSTP196

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Generalized linear models. Maximum likelihood theory. Exponential families of distributions. Logistic regression. Poisson regression. Loglinear models. Overdispersion. Quasilikelihood.

Last update: Kulich Ivan, Mgr., Ph.D. (26.04.2006)

Aim of the course -

Understand principles of parameter estimation and hypotheses testing

in a generalized linear model, apply the methods to build models to

address practical objectives, learn to interpret the results properly.

Last update: T_KPMS (20.05.2008)

Literature - Czech

Mc Cullagh, P. and Nelder, J.A.: Generalized Linear Models. 2nd Ed. Chapman and Hall, London, 1989.

Dobson, A.J.: An Introduction to Generalized Linear Models. CRC Press, Boca Raton, 1999.

Venables, W.N., Ripley, B.D.: Modern Applied Statistics with S. 4th Ed. Springer, New York, 2002.

Last update: Kulich Ivan, Mgr., Ph.D. (26.04.2006)

Teaching methods -

Lecture+exercises.

Last update: G_M (27.05.2008)

Syllabus -

Generalized linear models. Maximum likelihood theory. Exponential families of distributions. Logistic regression. Poisson regression. Loglinear models. Overdispersion. Quasilikelihood.

Last update: Kulich Ivan, Mgr., Ph.D. (26.04.2006)