Course module: Regression modelling for digital soil mapping

="width: 761px;" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack">Course title: Regression modelling for digital soil mapping Course Code:   Subject areas (Curriculum): Soil and environmental sciences Duration: 1 day Short description: This module introduces regression modelling for digital soil mapping, focussing on linear regression, CART and random forests modelling. Moderators: Bas Kempen Target audience: Soil and environmental scientists with an interest in quantitative methods for mapping soil and environmental properties. Requirements: Basic understanding of statistics; basic knowledge of the statistical software R Programme: Lecture (2h); Computer exercises (6h) Objective: Introducing regression modelling for digital soil mapping: model theory and assumptions, model selection, random forest modelling Software / materials:

R, RStudio

R packages: gstat, sp, randomForest, plyr, e1071, ggplot2, aqp, rgdal, GSIF, plotKML

Case studies: Edgeroi (Australia) Literature:   Minimum number of participants: 10 Maximum number of participants: 35
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