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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
<!-- Dear Programmer: -->
<!-- When I wrote this code, only god and I knew how it worked. -->
<!-- Now, only god knows it! Good Luck if you are trying to improve -->
<!-- this code!! -->
# FastMapping
<!-- badges: start -->
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![R-CMD-check](https://github.com/PPaccioretti/FastMapping/workflows/R-CMD-check/badge.svg)](https://github.com/PPaccioretti/FastMapping/actions)
<!-- badges: end -->
## A Shinny App for spatial analysis
FastMapping implements statistical tools for spatial data depuration,
quasi automatic variogram fitting and selection of the best geostatistical model
for kriging prediction by crossvalidation. As aid of result interpretation,
the program allows for prediction error statistics to be calculated and
visualized graphically. Input databases, should be composed of bidimensional
coordinates and the variable to be mapped.
## Installation
You can install FastMapping running:
``` r
devtools::install_github("PPaccioretti/FastMapping")
```
You can install the development version of FastMapping running in R:
``` r
devtools::install_github("PPaccioretti/FastMapping", ref = "pkg")
```
## Example
To use FastMapping you only need to run this code:
```{r example, eval = FALSE}
library(FastMapping)
FastMapping::run_app()
```
## Code of Conduct
Please note that the FastMapping project is released with a
[Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.