The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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 usage and a tutorial on package functions, please refer to fastFMM’s Vignette.
• For more extensive examples, see the Photometry Analysis Guide
  

Repository Folders

1. The ‘R’ folder contains the code of the package, including fui.R and plot_fui.R. The plot_fui.R is still under development and has not been widely tested.

2. 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 the README on the associated Github page photometry_FLMM for instructions on using fastFMM in Python through the Python packages rpy2 and fast_fmm_rpy2.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.