hmsidwR

This package provides the data used in the Health Metrics and the Spread of Infectious Diseases with R book

https://github.com/fgazzelloni/hmsidwr

Keywords

Repository

This package provides the data used in the Health Metrics and the Spread of Infectious Diseases with R book

README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

options(rmarkdown.html_vignette.check_title = FALSE)
```

# hmsidwR - Health Metrics and the Spread of Infectious Diseases



[![DOI](https://zenodo.org/badge/768163778.svg)](https://zenodo.org/badge/latestdoi/768163778) [![R-CMD-check](https://github.com/Fgazzelloni/hmsidwR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Fgazzelloni/hmsidwR/actions/workflows/R-CMD-check.yaml) [![CRAN status](https://www.r-pkg.org/badges/version/hmsidwR)](https://CRAN.R-project.org/package=hmsidwR)



The goal of `{hmsidwR}` is to provide the set of data used in the **Health Metrics and the Spread of Infectious Diseases Machine Learning Applications and Spatial Modelling Analysis** book. It also provides a set of functions to download data such as `getunz()`, and `gbd_get_data()` which allows the user to download data for the IHME SDG-API. With the `theme_hmsid()` is possible a customization of the ggplot2 theme, the `string_search()` function scan all folders and files to find a specific string. And, the `kbfit()` function fits a variogram model and then a set of kriging models to spatial data to select the best model based on metrics.

## Installation

``` r
install.packages("hmsidwR")
```

You can install the development version of `hmsidwR`, which might be always a bit more updated than the CRAN version, from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("Fgazzelloni/hmsidwR")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r load data, warning=FALSE, message=FALSE}
library(hmsidwR)
library(dplyr)
data(sdi90_19)
head(subset(sdi90_19, location == "Global"))
```

```{r example1}
sdi_avg <- sdi90_19 |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3))

head(sdi_avg)
```

```{r example2}
sdi90_19 |>
  filter(location %in% c("Global", "Italy", "France", "Germany")) |>
  group_by(location) |>
  reframe(sdi_avg = round(mean(value), 3)) |>
  head()
```

Owner

GitHub Events

Packages