Asymptotic Theory, Uppsala 2012

Starting November 5, I will give a course in asymptotic theory at the PhD level in Statistics. The course book is Ferguson, T.S. A Course in Large Sample Theory, Chapman and Hall 1996. Lectures are at 10.15-14 on Mondays, ending December 17. Examination is through take home exercises. For further information, see the attached schedule. Welcome to the course!

Rolf Larsson

Course Data
University: 
Uppsala
Offered: 
2012:2
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Regular schedule

Spatial Statistics (Winter Conference)

Course content

Introduction to spatial data analysis, representing space, interfacing geographical information systems, space-time data, spatial statistics overview (point patterns, geostatistics, areal data).
Use of GIS and spatial statistics for radioecological modeling and mapping using Chernobyl- and Fukushima-related data, focusing on public health protection.
Course Data
University: 
Örebro
Offered: 
2012:1
Level: 
PhD
Credits (ECTS): 
3
Type of schedule: 
Travel friendly schedule

Analysis of High-Dimensional Data

Jönköping International Business School, February 16-17, 2012

Welcome to a workshop on high-dimensional analysis, in particular if you are a research student or are supervising some with an interest in high-dimensional problems. The main idea is that we should learn who is doing what in this very interesting area. We interpret high-dimensional analysis in a very broad sense.

Advanced Probability and Inference

Content

  • Mathematical background (limits, series, order relations and rates of convergence, continuity, sets)
  • Measure theoretic foundations of probability (probability triplets, random variables, independence, expected values, change of variable)
  • Stochastic convergence (almost sure convergence, convergence in probability, convergence in distribution, laws of large numbers, central limit theorems, non-iid stochastic variables)
  • Conditional probability and expectation
  • Statistical tests (size and critical values, power, efficiency, asymptotic
Course Data
University: 
Örebro
Offered: 
2012:1
Level: 
PhD
Credits (ECTS): 
12
Type of schedule: 
Travel friendly schedule

Incomplete data: semi-parametric and Bayesian methods (Winter Conference)

Incomplete data is a common phenomenon in longitudinal studies based on surveys and/or population registers. In such studies individuals are followed through time and data may be incomplete due, e.g., to drop out/attrition (individuals intentionally leave the study, individuals leave the study because they move or die, etc.) and censoring (due to end of study, death, etc). Incomplete data may also arise due to selection mechanisms, for instance, in meta-analyses (publication bias) and causal inference in observational studies.
Course Data
University: 
Umeå
Offered: 
2011:1
Level: 
PhD
Credits (ECTS): 
3
Type of schedule: 
Travel friendly schedule

Multi level analysis

COURSE SYLLABUS Multi level analysis

Course Data
University: 
Linné
Offered: 
2010:2
Level: 
PhD
Credits (ECTS): 
8
Type of schedule: 
Travel friendly schedule

GRAPES workshop 2010 - Program

Program

All sessions are in the board room (Styrelserummet) on the third floor of Entréhuset (the leftmost building on the campus map).

Wednesday, Aug 11

 

Multivariate Analysis


Course Data
University: 
Uppsala
Offered: 
2010:1
Level: 
PhD
Credits (ECTS): 
15
Type of schedule: 
Travel friendly schedule

GRAPES workshop 2010

The first GRAPES workshop will be arranged on August 11-12, 2010 at Örebro university. The purpose of the workshop is to provide graduate students the opportunity to present and discuss their work.
  • Presentations by graduate students
  • Invited speaker: Professor David Hendry, University of Oxford
The GRAPES workshop is open to graduate students and faculty in Statistics and allied fields. Preference will be given to

Advanced Probability and Inference

Content

  • Mathematical background (limits, series, order relations and rates of convergence, continuity, sets)
  • Measure theoretic foundations of probability (probability triplets, random variables, independence, expected values, change of variable)
  • Stochastic convergence (almost sure convergence, convergence in probability, convergence in distribution, laws of large numbers, central limit theorems, non-iid stochastic variables)
  • Conditional probability and expectation
Course Data
University: 
Örebro
Offered: 
2009:2
Level: 
PhD
Credits (ECTS): 
12
Type of schedule: 
Travel friendly schedule

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