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README.Rmd
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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, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# ```fsdaR```
<!-- badges: start -->
[](https://cran.r-project.org/package=fsdaR)
[](https://github.com/UniprJRC/fsdaR/actions/workflows/R-CMD-check.yaml)
[](https://cran.r-project.org/package=fsdaR)
[](https://cran.r-project.org/package=fsdaR)
[](https://www.gnu.org/licenses/gpl-3.0.en.html)
<!-- badges: end -->
This package provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis
(FSDA)' which is comprehensive and computationally efficient
software package for robust statistics in regression, multivariate
and categorical data analysis. The current R version implements tools
for regression: (forward search, S- and MM-estimation, least trimmed
squares (LTS) and least median of squares (LMS)), for multivariate analysis
(forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression.
The distinctive feature of our package is the possibility of
monitoring the statistics of interest as a function of breakdown point,
efficiency or subset size, depending on the estimator. This is
accompanied by a rich set of graphical features, such as dynamic
brushing, linking, particularly useful for exploratory data analysis.
## Installation
The `fsdaR` package is on CRAN (The Comprehensive R Archive Network) and the latest release can be easily installed using the command
```
install.packages("fsdaR")
```
__NOTE (WINDOWS):__ To avoid some spurious errors due to the new MCR installation on Windows (V9.10), add the following to the system path
````
<RUNTIME_ROOT>\bin\win64
````
which most probably boils down to:
````
C:\Program Files\MATLAB\MATLAB Runtime\v910\bin\win64
````
## Building from source
To install the latest stable development version from GitHub, you can pull this repository and install it using
```
## install.packages("remotes")
remotes::install_github("UniprJRC/fsdaR")
```
Of course, if you have already installed `remotes`, you can skip the first line (I have commented it out).
On Windows, follow the __NOTE__ given above.
## Example
This is a basic example which shows you if the package is properly installed:
```{r example1}
library(fsdaR)
n <- 200
v <- 3
set.seed(123456)
X <- matrix(rnorm(n*v), nrow=n)
Xcont <- X
Xcont[1:5, ] <- Xcont[1:5,] + 3
out <- fsmult(Xcont, trace=TRUE) # no plots (plot defaults to FALSE)
names(out)
out <- fsmult(Xcont, trace=TRUE, plot=TRUE) # identical to plots=1
```