Submitted by Frank Miller on November 18, 2024 - 10:26
This course focuses on computational methods for optimisation, simulation and integration needed in statistics. The optimisation part discusses gradient based, stochastic gradient based, and gradient free methods. Further, constrained optimisation will be a course topic. We will discuss techniques to simulate efficiently for solving statistical problems. The course will start on March 11; course homepage (with full schedule): http://www.adoptdesign.de/frankmillereu/adcompstat2025.html.
This will be a PhD course in probability theory taught by Zangin Zeebari. The course wis only online. It will start in mid-November and a schedule is uploaded here. The syllabus contains information about content and litterature etc.
In an era of explosive growth in complex data, our course is your bridge to a deeper understanding of Functional Data Analysis (FDA) and Machine Learning (ML).
The main challenge today isn't data availability but rather our ability to interpret it. Join our growing community of professionals applying ML to tackle complex data challenges.
This crash course highlights key developments at the intersection of FDA and ML, with a focus on handling complex functional data. Moreover, as a student, you have the opportunity to earn 3 ECTS credits by submitting a report at the end of the workshop.
The goal of this summer course is to enhance students' understanding and skills in applied nonparametric econometrics. Initially, the course aims to provide a comprehensive foundation in nonparametric statistical methods. This is important for addressing the disconnect between economics and statistics in this field. This is a summer course that takes place between the 24th and 28th of June at Blekinge tekniska högskola.
This is a 7.5HP course for Ph.D. students in Statistics. It is planned as a traditional on campus blackboard lecture and exercise session course. The schedule is to be decided yet, but tentatively it will be blocked into two intensive ca week long blocks. Please email me directly, krzysztof_dot_bartoszek_at_liu_dot_se if you are interested in participating.
It is a 7.5HP course for Ph.D. students in statistics that is a core course for most if not all Ph.D. programs in Statistics. It is a hybrid course that can be followed online but in-class participation is also scheduled. The details about the course can be found here:
Submitted by podgorsk on September 10, 2023 - 12:17
In Fall II 2023, there will be offered a course in Statistical Inference I (7.5hp) for Ph.D. students in statistics and related fields. This initiative to have a national Ph.D. course has been taken by the departments of Statistics in Sweden and will be shared in the instruction duties by:
This will be a PhD course in probability theory taught by Zangin Zeebari. The course will be hybrid (with one mandatory start-up meeting). Please send an email to Kristofer Månsson before 19th of june if you are interested. (kristofer.mansson@ju.se). The syllabus contains information about content and litterature etc.
Submitted by Frank Miller on December 20, 2022 - 15:02
This course focuses on computational methods for optimisation, simulation and integration needed in statistics. The optimisation part discusses gradient based, stochastic gradient based, and gradient free methods. Further, constrained optimisation will be a course topic. We will discuss techniques to simulate efficiently for solving statistical problems. The course will start on March 16; course homepage (with full schedule): http://www.adoptdesign.de/frankmillereu/adcompstat2023.html.
