P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2025-07-13 05:21:50 +02:00
Code Releases Activity

(v1.5.0.9014) only_rsi_columns, is.rsi.eligible improvement

Browse Source
This commit is contained in:
dr. M.S. (Matthijs) Berends
2021-02-02 23:57:35 +01:00
parent 20d638c193
commit 2eca8c3f01
246 changed files with 1171 additions and 965 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
vignettes/resistance_predict.Rmd
View File

@ -21,7 +21,7 @@ knitr::opts_chunk$set(
```
## Needed R packages
As with many uses in R, we need some additional packages for AMR analysis. Our package works closely together with the [tidyverse packages](https://www.tidyverse.org) [`dplyr`](https://dplyr.tidyverse.org/) and [`ggplot2`](https://ggplot2.tidyverse.org) by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.
As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the [tidyverse packages](https://www.tidyverse.org) [`dplyr`](https://dplyr.tidyverse.org/) and [`ggplot2`](https://ggplot2.tidyverse.org) by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.
Our `AMR` package depends on these packages and even extends their use and functions.
@ -35,7 +35,7 @@ library(AMR)
```
## Prediction analysis
Our package contains a function `resistance_predict()`, which takes the same input as functions for [other AMR analysis](./AMR.html). Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.
Our package contains a function `resistance_predict()`, which takes the same input as functions for [other AMR data analysis](./AMR.html). Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.
It is basically as easy as:
```{r, eval = FALSE}