Material for Spatial Data Analysis in Practice - SDAP 2023 KTH, Sweden

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• Lecture 7. Scoping spatial statistics

• Lab 7. Thinking statistically and thinking spatially: an illustration

  • Material for Lab 7

  
  

• Lecture 8. Introduction to Bayesian Inference

• WinBUGS-help

• Lab 8. Introduction to WinBUGS

  • Material for Lab 8

  
  

• Lecture 9. Fitting Bayesian hierarchical models for continuous valued response data in WinBUGS

• Lab 9. Fitting Bayesian hierarchical models for continuous valued response data in WinBUGS

  • Material for Lab 9

  
  

• Lecture 10. Fitting Bayesian hierarchical models for discrete valued response data in WinBUGS

• Lab 10. Fitting Bayesian hierarchical models for discrete valued response data in WinBUGS

  • Material for Lab 10

  
  

• The Peterborough data in Lab 10 in Excel format for data formatting demo

  
  

• Lecture 11. Further topics in modelling spatial data

• Lab 11. Ecological modelling of small area health data using Bayesian spatial models

  
  

• Lecture 12. Modelling small area spatial-temporal data: an introduction

• Lab 12. Modelling (small area) time series data in WinBUGS

  • Material for Lab 12

  
  
  

• Lecture 13. Developing Bayesian hierarchical models for small area space-time data

• Lab 13. Model development for analysing space-time data (Part 1): fitting a separable spatial-temporal model in WinBUGS

  • Material for Lab 13

  
  

• Lecture 14. Applications in Spatial-Temporal Modelling

• Lab 14. Model development for analysing space-time data (Part 2): fitting an advanced spatial-temporal model in WinBUGS

  • Material for Lab 14

  
  

#### R code to read a dataset in Excel format and
#### export it to a file in the WinBUGS list format
#### block 1 requires the excel data to be exported to a csv file
#### block 2 reads in the Excel file directly without the need to export
#### (use block 2!)

####   block 1
in.file <- "c:/demo_WinBUGS_data_formatting.csv"
out.file <- "c:/ForWinBUGS.csv"
data <- read.csv(in.file,header=TRUE)
data <- lapply(data,function(x){as.numeric(x)})
dput(data,out.file)


####   block 2
#  if you can install packages in R,
#  you do not need to convert an Excel file to csv manually
install.packages("readxl")
library(readxl)
in.file <- "c:/demo_WinBUGS_data_formatting.xlsx"
out.file <- "c:/ForWinBUGS.csv"

data <- read_excel(in.file)
data <- lapply(data,function(x){as.numeric(x)})
dput(data,out.file)