A project package to estimate a poverty map for Burundi
# Poverty Mapping in Burundi : Reproducability Guidelines
The goal of bdipovmap is to create a poverty map for Burundi using the
Small Area Estimation approach of the Fay Herriot Model (Fay and
Herriot, 1979). This ReadMe shows how to reproduce all the tables and
results in the paper. You can find the script that generates this readme
file as “README.Rmd” in this github working directory.
## System Set-Up
1) Please clone the repository and open up the project within RStudio.
Make sure you are in the project environment. In the top right
corner you will see the “bdipovmap” beside the R logo to show you
are in the project’s environment. This is extremely important.
Otherwise you cannot automatically load the user defined functions.
2) Please install the R `devtools` package, run
`install.packages("devtools")`
3) Open `README.Rmd` and go ahead and knit the Markdown file. This file
is basically running the script that produces the poverty map.
Please see code and outputs below:
#> ℹ Loading bdipovmap
#> Spherical geometry (s2) switched off
#>
#> Saving 7 x 5 in image
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> Saving 7 x 5 in image
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> although coordinates are longitude/latitude, st_intersects assumes that they
#> are planar
#>
#> Non-sampled domains exist.
#>
#> Please note that the model selection criteria are only computed based on the in-sample domains.
#>
#> Please note that the model selection criteria are only computed based on the in-sample domains.
#>
#> Please note that the model selection criteria are only compu …