Fast Functional Mixed Models using Fast Univariate Inference.
fastFMM: Fast Functional Mixed Models using Fast Univariate Inference (FUI)
Repository Description
Repository for the development version of the R Package fastFMM
. For more information, see the official fastFMM
$\texttt{CRAN}$ site.
fastFMM
R Package
Installation
Download the $\texttt{R}$ Package fastFMM
by running the following command within $\texttt{R}$ or $\texttt{RStudio}$:
install.packages("fastFMM", dependencies = TRUE)
Alternatively, the development version of the $\texttt{R}$ Package fastFMM
can be downloaded as follows:
library(devtools)
install_github("gloewing/fastFMM")
Package Usage
For the usage and a tutorial on package functions, please refer to fastFMM's Vignette.
Repository Folders
The 'R' folder contains the code of the package, including
fui.R
andplot_fui.R
. Theplot_fui.R
is still under development and has not been widely tested.The 'vignettes' folder contains a vignette which shows how to use different arguments of the
fui
function. This vignette can also be viewed in the link above (under Package Usage).
Dataset Links
The example data set is available in the 'vignettes' folder under the name 'time_series.csv'.
Calling fastFMM from Python
See 'python_fastFMM_vignette.py' in the Github repo for a brief example of using fastFMM
on Python through the Python package rpy2
. We are working on more documentation. The tutorial assumes the fastFMM
R package (and all its dependenices), and the rpy2
Python package have already been installed. Even if you intend to use the package purely within Python, it may be helpful to first install fastFMM
in RStudio to ensure all package dependenices are installed automatically.