Compute the average of a sequence of random vectors
  in a moving expanding window using a fixed amount of memory.

Color palettes inspired by the works of 
  Mexican painters and muralists. The package includes functions that
  return vectors of colors and also functions to use color and fill
  scales in 'ggplot2' visualizations.

Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty). A detailed description of the package functionalities is provided in Charvat and Belot (2021) <doi: 10.18637/jss.v098.i14>.

A color palette generator inspired by Mexican politics, with 
    colors ranging from red on the left to gray in the middle and green on the 
    right. Palette options range from only a few colors to several colors, but with
    discrete and continuous options to offer greatest flexibility to the user. 
    This package allows for a range of applications, from mapping brief discrete scales 
    (e.g., four colors for Morena, PRI, and PAN) to continuous interpolated arrays 
    including dozens of shades graded from red to green.

The method 'm:Explorer' associates a given list of target genes (e.g. those involved in a biological process) to gene regulators such as transcription factors. Transcription factors that bind DNA near significantly many target genes or correlate with target genes in transcriptional (microarray or RNAseq data) are selected. Selection of candidate master regulators is carried out using multinomial regression models, likelihood ratio tests and multiple testing correction. Reference: m:Explorer: multinomial regression models reveal positive and negative regulators of longevity in yeast quiescence. Juri Reimand, Anu Aun, Jaak Vilo, Juan M Vaquerizas, Juhan Sedman and Nicholas M Luscombe. Genome Biology (2012) 13:R55 <doi:10.1186/gb-2012-13-6-r55>.

Provide simple functions to (i) compute a class of 
  multi-functionality measures for a single ecosystem for given 
  function weights, (ii) decompose gamma multi-functionality 
  for multiple ecosystems into a within-ecosystem component 
  (alpha multi-functionality) and an among-ecosystem component 
  (beta multi-functionality). In each case, the correlation 
  between functions can be corrected for. Based on biodiversity 
  and ecosystem function data, this software also facilitates 
  graphics for assessing biodiversity-ecosystem functioning 
  relationships across scales.