Seminar held by:
Tomas Formanek
Department of Econometrics
Faculty of Informatics and Statistics
University of Economics, Prague

• Detailed information provided here (CZE)
• Literature and other supporting materials for the course

• Detailed information provided here (CZE)

• Detailed information provided here (CZE)

• Data manipulation and visualization basics
• Markdown and Quarto for data & output presentation
• Introduction to Tidyverse packages tidyr, dplyr, ggplot2, pipe operator %>%
• Importing data from major databases (Eurostat, IMF, Yahoo finance, etc.)
• Missing data, multiple imputation

• Download presentation slides for Block 1
• Download R scripts (zip)

• R / RStudio

• stackoverflow

• Enders, C.K., Applied Missing Data Analysis (2022)

• Spatial data: basic descriptive analysis
• Spatial data: advanced visualization (choropleths, sf package)
• Spatial econometrics
  • Cross-sectional data
  • Panel data
  • Advanced topics (spatial filtering)

• Download presentation slides for Block 2
• Download R scripts (zip)
• Rowe and Arribas-Bel, Spatial Modelling for Data Scientists - a textbook

• Simple Features for R

• GADM maps and data

• Interactive Course using mgcv (ch. 3)

• R Package RCzechia : run install.packages("RCzechia")

• Spatial autocorrelation - RPubs tutorial

• Introduction to CS spatial regression models

• ARSET - Fundamentals of Remote Sensing (NASA on-line course)

• ARSET - Applied Remote Sensing (NASA on-line courses)

Model selection

• Theoretical approach: specific-to-general, general-to-specific
• Stepwise model selection

Model selection & regularization

• Penalized regression
• Dimension reduction: PCR & PLS

Moving beyond linearity

• Quantile regression (quick repetition)
• Polynomial and step regression
• Regression splines, smoothing splines
• Local regression
• Generalized Additive Models (GAM)

• Download presentation slides for Block 3
• Download R scripts (zip)

• Interactive Course using mgcv (ch. 1,2,4)
• Quantitude podcast S3E03 Principal Components Analysis is your PAL

• Introduction to linear mixed effects models
  • Longitudinal data
  • Hierarchical models

• Download presentation slides for Block 4
• Download R scripts (zip)

• Introduction to LMEs in R
• Mixed models in R
• Vignettes for lme4 package

• Presentation slides based on Block 6 of 4EK416/4EK608
• Download R scripts (zip)

• R package effects
• R package effects for multinomial and proportional-odds logit models

• Ben Lambert: A graduate course in econometrics, videos 54 to 74

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