Advanced Bayesian Learning, 7.5 credits

This is an advanced course in Bayesian statistics for PhD students in statistics, computer science, the engineering sciences and other related fields.
The course is divided into 3-5 contemporary topics in Bayesian analysis, and the choice of topics can vary from year to year depending on the research frontier.
The planned topics for the current year are (preliminary and subject to change):

1. Gaussian Processes with Applications
2. Bayesian Nonparametrics
3. (Stochastic) Variational Inference
4. Bayesian Model Inference

Course Data
University: 
Stockholm
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

PhD course in Econometrics, 15 ECTS credits, spring 2020

All lectures are located to Växjö campus, Linnaeus University. The course is arranged in six blocks of lectures to facilitate for commuting students. Apart from traditional white-board lectures, there will also be computer classes to ensure a strong connection to empirical econometric modelling.

Course Data
University: 
Linné
Offered: 
2020:1
Level: 
PhD
Credits (ECTS): 
15
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

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

Causal inference

 

Course Data
University: 
Umeå
Offered: 
2018:2
Level: 
Master
PhD
Credits (ECTS): 
8
Type of schedule: 
Regular schedule

Ph.D. course in Statistical Inference HT2018-VT2019

Ph.D. course in Statistical Inference (15 hp) for students in
Statistics, Mathematical Statistics, and related areas.

Course Data
University: 
Linné
Offered: 
2018:2
Level: 
PhD
Credits (ECTS): 
15
Type of schedule: 
Travel friendly schedule

Wavelets for Time Series Analysis (May 2018)

Course Code: 3FNA023
ECTS credits: 5
Level Doctoral course
Course contents
The course will cover the following topics:
- an introduction to wavelet analysis
- the Discrete Wavelet Transform (DWT)
- the Maximal Overlap DWT (MODWT)
- the wavelet variance, covariance, correlation and cross correlation

Course Data
University: 
Linné
Offered: 
Not scheduled
Level: 
PhD
Credits (ECTS): 
5
Type of schedule: 
Travel friendly schedule

Approximate Bayesian Computation

Approximate Bayesian Computation (ABC) is an increasingly popular inference paradigm in applications where traditional (Bayesian or frequentist) inference is difficult because the likelihood function is e.g. computationally costly to evaluate or unavailable in closed, tractab- le form. In the course, we will start by briefly studying traditional Bayesian inference and different kinds of simulation-based inference methods in general.

Course Data
University: 
Chalmers
Offered: 
Not scheduled
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Schedule to be decided

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