Courses

Introduction to Structural Equation Models (7.5 ECTS)

Upon completion of the course, the doctoral student will be able to: explain the basic theoretical foundation and practical use of Structural Equation Models (SEM), apply SEM on real problems, interpret and present the results, estimate structural equation models with maximum likelihood and least squares and be able to evaluate the results.

Course Data
University: 
Dalarna
Offered: 
2020:2
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Schedule to be decided

Statistical Inference I (7.5 hp)

A Ph.D. course in modern statistical inference theory for students in statistics, mathematical statistics, and related areas. Two onsite meetings (Lund and Stockholm) and three online meetings. The details about the course can be found at https://krys.neocities.org/Teaching/StatInf/PhD_stat_inf.html.

Course Data
University: 
Lund
Offered: 
2020:2
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Travel friendly schedule

Optimisation algorithms in Statistics I, 4 credits

We will discuss algorithms to compute minima or maxima which are frequently needed in statistics and machine learning. Topics of lectures on four occasions: gradient based algorithms, stochastic gradient based algorithms, gradient free algorithms (e.g. particle swarm optimisation), handling of restrictions during optimisation. Course homepage: http://www.adoptdesign.de/optimisation1.html

Course Data
University: 
Stockholm
Offered: 
2020:2
Level: 
PhD
Credits (ECTS): 
4
Type of schedule: 
Travel friendly schedule

Dependence modelling using vine copulas: theory and applications

All lectures are online via Zoom. The lecturer is Prof. Dr. Claudia Czado (https://www.professoren.tum.de/en/czado-claudia/) who also wrote the course book. Info regarding the course is available in the attached course plan. The course will take place in the last week of august (detailed schedule is attached). Any questions contact Kristofer Månsson (kristofer.mansson@ju.se).

 

Course Data
University: 
Jönköping
Offered: 
2020:2
Level: 
PhD
Credits (ECTS): 
5
Type of schedule: 
Travel friendly schedule

Large sample theory

Due to the outbreak of the coronavirus all lectures will be online via Zoom.The lecturer is Dr. Abdul Aziz Ali. Info regarding the course is available in the attached course plan. The course will start in the midle of may. Any questions contact Kristofer Månsson (kristofer.mansson@ju.se).

Course Data
University: 
Jönköping
Offered: 
2020:1
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Travel friendly schedule

Stochastic differential equations with R school

At the Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University, 14th-19th May 2020 we will be hosting a school concerning stochastic differential equations and the YUIMA R package (Simulation and Inference for SDEs and Other Stochastic Processes, https://cran.r-project.org/web/packages/yuima/index.html). The lectures will be given by members of the YUIMA team ( https://yuimaproject.com/ ).

Course Data
University: 
Linköping
Offered: 
2020:1
Level: 
Master
PhD
Credits (ECTS): 
0
Type of schedule: 
Travel friendly schedule

Topics in Time Series Analysis: Old to New

During the fall 2019 professor Richard Davis, Columbia University, will give a course on Topics in Time Series Analysis: Old to New.

The course is aimed at advanced masters students and PhD students from Chalmers and Gothenburg University, and also welcomes students from other Scandinavian universities. The first meeting will be 

Monday, September 23, 13:15-15:00, room MVH 12 in the Mathematics Building, Chalmers tvärgata 3

Course Data
University: 
Chalmers
Offered: 
2019:2
Level: 
Master
PhD
Credits (ECTS): 
5
Type of schedule: 
Schedule to be decided

Bayesian Statistics I

This masters course introduces basic concepts, ideas and methods of Bayesian inference. It is given in the late fall at Stockholm University as part of the masters programme and in the late spring at Linköping University (then under the name Bayesian Learning) as part of the master's course in the programme 'Statistics and Machine Learning'. The focus is on models and methods in the field of machine learning, but most of the course content is of general statistical interest.
The course will be in English.

Course Data
University: 
Stockholm
Offered: 
2019:2
Level: 
Master
PhD
Credits (ECTS): 
8
Type of schedule: 
Regular schedule

Topics in philosophy of science and statistical inference

The Department of Statistics at Uppsala University plans to give an introductory PhD course in philosophy of science in May-June and August-September 2019, see attached file.

Course Data
University: 
Uppsala
Offered: 
2019:1
Level: 
PhD
Credits (ECTS): 
5
Type of schedule: 
Travel friendly schedule

Some asymptotic methods in statistical inference

The aim is to provide some theory concerning asymptotic methods of statistics and probability with applications to inference problems. Knowledge of measure theory is not needed. Basic convergence concepts and results (with proofs) such as the Lindeberg-Lévy central limit theorem should have been covered in previous courses.
To sign up for the course send an e-mail to per.gosta.andersson@stat.su.se

 

Course Data
University: 
Stockholm
Offered: 
2019:1
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Travel friendly schedule

Pages