Lagged Cross-Correlation Analysis of Environmental Time Series
Overview
Tools for analysing lagged relationships between environmental variables and ecological or epidemiological time series. The package implements a workflow to aggregate meteorological data over multiple lagged intervals, fit regression models, including mixed-effect models using 'glmmTMB', for each lag window, and visualise varied models outcomes (effect strength and direction, model prediction error...) using cross-correlation maps ('CCM').
Bug fixes
- Correct default value for arg
shiftinecoXCorr()function (from -1 to 1)
Improvements
- Correct R code output of the shiny app.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK7 OK2026-03-25
Documentation
- Help pages
- 8 (1 internal)includes a package overview page
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 80%
- Documented parameters
- 93%
- Return-value docs
- 100%
- Help pages citing references
- 38% with a bibliography file
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 0
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Releases over time
3 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/nmoiroux/ecoxcorr on 2026-10-21.
Dependencies
Installing ecoXCorr adds 83 packages (47 with compiled code, 86 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, bslib 5.6 MB.
CRAN will archive these unless their check problems are fixed by the date shown. This package needs each one to install.
- insight through performancefix by Nov 14
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2026-03-24
- Total releases
- 3 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 14 KB / 2 files
- Download size
- 162 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("ecoXCorr")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.5281/zenodo.18600567.
The repository also keeps a CITATION.cff.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.