Can detect relatively weak spatial genetic patterns by using Moran's Eigenvector Maps (MEM) to extract only the spatial component of genetic variation.  Has applications in landscape genetics where the movement and dispersal of organisms are studied using neutral genetic variation.

A simple way to construct and maintain functions that keep state i.e. remember their argument lists. This can be useful when one needs to repeatedly invoke the same function with only a small number of argument changes at each invocation.

An infrastructure for the management of survey data including
        value labels, definable missing values, recoding of variables,
        production of code books, and import of (subsets of) 'SPSS' and
        'Stata' files is provided. Further, the package allows to produce
        tables and data frames of arbitrary descriptive statistics and
        (almost) publication-ready tables of regression model
        estimates, which can be exported to 'LaTeX' and HTML.

A simple in-memory, LRU cache that can be wrapped
    around any function to memoize it. The cache is keyed on a hash of the input data (using 'digest') or on pointer equivalence.

A simple way to memoize function results to improve performance by eliminating unnecessary computation or data retrieval activities.

Producing high-quality documents suitable for publication directly from R is made possible by the R Markdown ecosystem.
  'memoiR' makes it easy.
  It provides templates to knit memoirs, articles and slideshows with helpers to publish the documents on GitHub Pages and activate continuous integration.

Cache the results of a function so that when you
    call it again with the same arguments it returns the previously computed
    value.

A 'rmarkdown' template that supports company logo, contact info, 
    watermarks and more. Currently restricted to 'Latex'/'Markdown'; a similar 
    'HTML' theme will be added in the future.

Tools to quantify ecological memory in long time-series with Random Forest models (Breiman 2001 <doi:10.1023/A:1010933404324>) fitted with the 'ranger' library (Wright and Ziegler 2017 <doi:10.18637/jss.v077.i01>). Particularly oriented to palaeoecological datasets and simulated pollen curves produced by the 'virtualPollen' package, but also applicable to other long time-series involving a set of environmental drivers and a biotic response.