Statistik

Spatial data has become ubiquitous in a myriad of different disciplines and poses substantial challenges to both applied scientist and statisticians. Such data arises i.e. in  climatology or environmental sciences (where different weather characteristics such as temperature, humidity etc are recorded at fixed locations), in economics or political sciences (where housing prices or election results are collected at ZIP level) as well as in  criminology and forestry (where the locations of crime events or tree stands are of interest). Recently, spatial data on structured domains i.e. roads or railway systems or on the sphere have stimulated a immense interest.

This seminar is designed to provide a thorough treatment of all different subtypes of  spatial data  on both the spatial and more complex domains (e.g. networks)  including (1) geostatistics, (2) spatial areal data, and (3) Spatial point patterns as special cases. Particular interest is put on the analysis of spatial point processes which have become an highly attractive field of research. Good knowledge of statistics including topics such as regression, time series or stochastics  is recommended for this course. Topics literature and times will be fixed in an initial ZOOM meeting.

This seminar is restricted to 20 participants and requires personal registration via Email to m.eckardt@hu-berlin.de, latest April, 5th.

Due to the overlap in content, students who have taken and passed the lecture (VL + UE)  "Selected Topics in Statistics, Topic Spatial Statistics" (7010327) in the summer semester 2020 cannot take this seminar

This module gives a thorough introduction to both (main) general approaches to derive solutions for the statistical inference problems: Likelihood-based inference and Bayesian inference.

Joint research seminar of the Chair of Statistics and the Chair of Econometrics