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.
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.
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, asy
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.
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
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)