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TimeTraits

TimeTraits provides a set of tools for analysing biological time-series data using functional data analysis (FDA). The package is designed to support end-to-end workflows, from smoothing rhythmic time series to extracting group-level traits from functional principal component analysis (FPCA).

The methods implemented here are particularly suited to circadian and other biological time-series data where interest lies in comparing functional patterns across experimental groups, time windows, or curve derivatives.

Features

• Smoothing of biological time-series data using functional data representations
• Functional principal component analysis (FPCA) of smoothed curves
• Extraction of group-level FPCA-derived traits
• Support for multiple curve derivatives (e.g. 0th, 1st, 2nd)
• Optional temporal segmentation (e.g. pre/post environmental shifts)
• Shape-based outlier detection (where applicable)

Installation

You can install the development version of TimeTraits directly from GitHub:

```r # install.packages(“devtools”) devtools::install_github(“scllock/TimeTraits”)

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.