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memoria: Quantifying Ecological Memory in Palaeoecological Datasets and Other Long Time-Series

Quantifies ecological memory in long time-series using Random Forest models ('Benito', 'Gil-Romera', and 'Birks' 2019 <doi:10.1111/ecog.04772>) fitted with 'ranger' (Wright and Ziegler 2017 <doi:10.18637/jss.v077.i01>). Ecological memory is assessed by modeling a response variable as a function of lagged predictors, distinguishing endogenous memory (lagged response) from exogenous memory (lagged environmental drivers). Designed for palaeoecological datasets and simulated pollen curves from 'virtualPollen', but applicable to any long time-series with environmental drivers and a biotic response.

Version: 1.1.0
Depends: R (≥ 4.1.0)
Imports: ggplot2, ranger, zoo, rlang
Suggests: spelling, testthat
Published: 2026-02-10
DOI: 10.32614/CRAN.package.memoria
Author: Blas M. Benito ORCID iD [aut, cre, cph]
Maintainer: Blas M. Benito <blasbenito at gmail.com>
License: MIT + file LICENSE
URL: https://blasbenito.github.io/memoria/
NeedsCompilation: no
Language: en-US
Citation: memoria citation info
Materials: NEWS
CRAN checks: memoria results

Documentation:

Reference manual: memoria.html , memoria.pdf

Downloads:

Package source: memoria_1.1.0.tar.gz
Windows binaries: r-devel: memoria_1.0.0.zip, r-release: memoria_1.0.0.zip, r-oldrel: memoria_1.0.0.zip
macOS binaries: r-release (arm64): memoria_1.1.0.tgz, r-oldrel (arm64): memoria_1.1.0.tgz, r-release (x86_64): memoria_1.1.0.tgz, r-oldrel (x86_64): memoria_1.1.0.tgz
Old sources: memoria archive

Linking:

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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.
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