Agenda
Handling Spatial Data in R
Classes for Spatial Data in R - Visualising Spatial Data: The Traditional Plot System, Trellis/Lattice Plots, Interactive Plots, Colour Palettes and Class Intervals - Spatial Data Import and Export: Coordinate Reference Systems, Vector File Formats, Raster File Formats, Google Earth, Google Maps, Geographical Resources Analysis Support System (GRASS) - Map Overlay or Spatial Join - R-Packages: rdgal, spplot and ggplot, latticeExtra, raster, rgeos
Spatio-Temporal Data
Types of Spatio-Temporal Data - Handling Time Series Data - Selection, Addition, and Replacement of Attributes - Overlay and Aggregation - Visualization: Multi-panel Plots, Space-Time Plots, Animated Plots, Time Series Plots - R-Packages: xts, spacetime
Analyzing Spatial Data
Preliminary Analysis of a Point Pattern: G Function (Distance to the Nearest Event), F Function (Distance from a Point to the Nearest Event) - Statistical Analysis of Spatial Point Processes: Homogeneous and Inhomogeneous Poisson Processes, Estimation of the Intensity, Likelihood of an Inhomogeneous Poisson Process - Applications in Spatial Epidemiology: Case–Control Studies, Binary Regression, Accounting for Confounding and Covariates - R-Packages for the Statistical Analysis of Spatial Data: spatial, maptools, splancs, spatstat,
Interpolation and Geostatistics
Exploratory Data Analysis - Non-geostatistical Interpolation Methods - Estimating Spatial Correlation using the Variogram: Exploratory Variogram Analysis, Cutoff, Lag Width, Direction Dependence, Variogram Modelling, Multivariable Variogram Modelling - Spatial Prediction: Universal, Ordinary, and Simple Kriging, Kriging in a Local Neighbourhood, Multivariable Prediction: Cokriging, Trend Functions and Their Coefficients, - Kriging, Filtering, Smoothing - Model Diagnostics: Cross Validation Residuals, Cross Validation z-Scores, Multivariable Cross Validation - Geostatistical Simulation
Modelling Areal Data
Spatial Neighbours and Spatial Weights - Testing for Spatial Autocorrelation - Fitting Models of Areal Data
Trainer
Marco Skulschus (born in Germany in 1978) studied economics in Wuppertal (Germany) and Paris (France) and wrote his master´s thesis about semantic data modeling. He started working as a lecturer and consultant in 2002.
Publications
- Grundlagen empirische Sozialforschung ISBN 978-3-939701-23-1
- System und Systematik von Fragebögen ISBN 978-3-939701-26-2
- Oracle PL/SQL ISBN 978-3-939701-40-8
- MS SQL Server - T-SQL Programmierung und Abfragen ISBN 978-3-939701-69-9
Projects
- He works as an IT-consultant and project manager. He developed various Business Intelligence systems for industry clients and the public sector. For several years now, he is responsible for a BI-team in India which is mainly involved in BI and OLAP projects, reporting systems as well as statistical analysis and Data Mining.
Research
He led several research projects and was leading scientist and project manager of a publicly funded project about interactive questionnaires and online surveys.