Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
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401-3627-00L  High-Dimensional Statistics

SemesterAutumn Semester 2016
LecturersP. L. Bühlmann
Periodicitytwo-yearly recurring course
CourseDoes not take place this semester.
Language of instructionEnglish



Catalogue data

Abstract"High-Dimensional Statistics" deals with modern methods and theory for statistical inference when the number of unknown parameters is of much larger order than sample size. Statistical estimation and algorithms for complex models and aspects of multiple testing will be discussed.
ObjectiveKnowledge of methods and basic theory for high-dimensional statistical inference
ContentLasso and Group Lasso for high-dimensional linear and generalized linear models; Additive models and many smooth univariate functions; Non-convex loss functions and l1-regularization; Stability selection, multiple testing and construction of p-values; Undirected graphical modeling
LiteraturePeter Bühlmann and Sara van de Geer (2011). Statistics for High-Dimensional Data: Methods, Theory and Applications. Springer Verlag.
ISBN 978-3-642-20191-2.
Prerequisites / NoticeKnowledge of basic concepts in probability theory, and intermediate knowledge of statistics (e.g. a course in linear models or computational statistics).

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersP. L. Bühlmann
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 20 minutes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
401-3627-00 VHigh-Dimensional Statistics
Does not take place this semester.
2 hrsP. L. Bühlmann

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Doctoral Department of MathematicsGraduate SchoolWInformation
Mathematics BachelorSelection: Probability Theory, StatisticsWInformation
Mathematics MasterSelection: Probability Theory, StatisticsWInformation
Computational Science and Engineering BachelorElectivesWInformation
Computational Science and Engineering MasterElectivesWInformation
Statistics MasterStatistical and Mathematical CoursesWInformation