Geo-Statistical Modeling of Spatially Referenced Data.
RiskMap
The goal of RiskMap
is to provide a set of functions for visualisation, processing and likelihood-based analysis of geostatistical data.
Installation
You can install the development version of RiskMap from GitHub with:
# install.packages("devtools")
devtools::install_github("claudiofronterre/RiskMap")
Example
This is a basic example which shows you how to solve a common problem:
library(RiskMap)
## basic example code
What is special about using README.Rmd
instead of just README.md
? You can include R chunks like so:
summary(cars)
#> speed dist
#> Min. : 4.0 Min. : 2.00
#> 1st Qu.:12.0 1st Qu.: 26.00
#> Median :15.0 Median : 36.00
#> Mean :15.4 Mean : 42.98
#> 3rd Qu.:19.0 3rd Qu.: 56.00
#> Max. :25.0 Max. :120.00
You’ll still need to render README.Rmd
regularly, to keep README.md
up-to-date. devtools::build_readme()
is handy for this. You could also use GitHub Actions to re-render README.Rmd
every time you push. An example workflow can be found here: https://github.com/r-lib/actions/tree/v1/examples.
You can also embed plots, for example:
In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub and CRAN.
Estimation function design
How should the user specify the model?
# OPTION 1
y ~ rainfall + gp(x, y) + re(id_school) + re(id_region)
# Arguments for gp function
gp(long = NULL, lat = NULL, kappa = (numeric_value, default = 0.5), nugget = c(T = default, F, fixed_numeric_value), ...)
# Arguments for re function
re(numeric or categorical variable, ...) only needs an index in the dataset
glgm <- function(formula,
distr_offset = NULL,
cov_offset = NULL,
data,
family,
convert_to_crs = NULL,
scale_to_km = TRUE,
control_MCMC = NULL,
S_samples = NULL,
save_samples = F,
messages = TRUE)
My solution to incorporate "gp" into the formula
(tf <- terms(y ~ x + x:z + gp(kappa = 0.5, nugget = TRUE)+w, specials = "gp"))
attr(tf, "specials") # index 's' variable(s)
gp <- rownames(attr(tf, "factors"))[[attr(tf, "specials")$gp]]
gp_list <- eval(parse(text = gsub("gp","list",gp)))
gp_list