Information

• Course Outline / Syllabus
• Prerequisite - topics covered in CVEN5454

• Elements of Statistical Learning
• An Introduction to Statistical Learning with R
  
• Lecture Slides / Videos
• Spatio-Temporal Statistics with R
• Graphical Neural Networks
• Statistical Rethinking - Book
• Applied Spatial Data Analysis with R - Springer
• Hands on Machine Learning with R
  

• Simple Linear Regression
• Multiple Regression
• Prof. Lall's Regression Notes
• Helsel's online book

• Prof. Rodriguez GLM Page - Notes, R etc
• Bookdown - Roback and Legler
  
• Reference: Prof. C. Czado-TUM-GLM-Lectures
• Generalized Linear Models - Fahrmeir and Tutz

• Beyond Linearity
• Variable Selection, Lasso, Spline etc.
  
• Loader Book Online - Springer
  
• Local Regression and Likelihood
• Loader - Chaps 2&3
• Loader - Chaps 4&5
• Lecture Notes (John Fox)
• Smoothing Techniques in R
  

• R project
• R Studio
• Datacamp
  
• Very Good R-tutorial - Thomas Jagger
  
  • Hurricane Data and Refs Page
    
• Catherine Dressler Report
• R-tutorial documents
• Spatial Data Visualization
• Springer R-books
• BookDowns
  

• Homework #1 (1/13 - 2/13, 2026)

• Simple Linear Regression
• R-tutorial on simple linear regression
  
• R Commands
  
• Multiple Linear Regression
• R-tutorial on Multiple Linear Regression
  
• R commands
  
• Model Diagnostics
  
• Confidence and Prediction Interval
• Nonparametric confidence intervals
  
• Logistic Regression

•  1 and 2 variable data sets
• Fit a best local polynomial model (using GCV)
• Perform model diagnostics
• Estimate the function at several locations
• Plot/Map the estimates and error variance

R-JAGS Manual

•  Spatial Bayesian Hierarchical Modeling
• Code/commands for results in Verdin et al. (2015)
  
• STAN examples
• spBayes - R Package

• Extreme Value Analysis (GEV+Cov)
  
• Towler et al. (2010)
• Bracken et al. (2018, WRR)
• Van dusen et al. (2020, Climate Risk Mgmt)

• May-Ostendorp et al. (2011) - Building Energy
• Esmaeili et al. (2015) - Construction Safety
• Kohler et al. 2016 (Weibull GLM)
• Weirich et al. 2015 (Gamma GLM + Markov)
• Weirich et al. 2011 (GLM - Gamma + Logistic)

Local Polynomial Applications

•  Seasonal Streamflow Forecast      
  
• Grantz et al. (2005)
• Bracken et al., (2010)
  
• Streamflow Simulation
• Prairie et al. (2005)
• Review paper on forecasting and Simulation
• Rajagopalan et al. (2005)
  
• Water Quality Modeling (Local GLM)
  
• Towler et al., 2010 (Local Logistic)
  
• Towler et al., 2009 (Local Poly)
• Towler et al., 2013 (Local Poisson)
• Samson et al., 2016 (Local Gamma)

GAM & Bayesian Dynamic Regression

• Krishnaswamy et al (2015)- Monsoon-ENSO-IOD
• Supplemental

Hierarchical Modeling in Space - Kriging

• Kriging, Local Polynomial for Blending
• Verdin et al. (2016)
  
• Bayesian - Satellite + Observed Precip Blending
• Verdin et al. (2015)
• Spatial Hierarchical - Waste Water Treatment
• Suchetana et al. (2016)
• Bayesian - Spatial Extremes
• Bracken et al. (2016)
• Ossondon et al. (2021, J. Hydrol)
• Ossondon et al. (2021, WRR) 
• Ossondon et al. (2021, HESS)
  
• Bayesian Logistic Regression
• Horvath et al. (2020)
  
• Stochastic Precipitation, Temp & Weather Gen
• Weather Gen - Verdin et al. 2014
• Spatial Precip Generator - Kleiber et al. 2012
• Spatial Temp. Generator - Kleiber et al. 2013