Nothing
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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Blas M. Benito [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-5105-7232>) |
| Maintainer | Blas M. Benito <blasbenito@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.1.0 |
| URL | https://blasbenito.github.io/memoria/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the memoria package in your browser
Any scripts or data that you put into this service are public.
