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growthTrendR  

Toolkit for Data Processing, Quality, and Statistical Models
View on CRAN: Click here


Download and install growthTrendR package within the R console
Install from CRAN:
install.packages("growthTrendR")

Install from Github:
library("remotes")
install_github("cran/growthTrendR")

Install by package version:
library("remotes")
install_version("growthTrendR", "0.2.2")



Attach the package and use:
library("growthTrendR")
Maintained by
Xiao Jing Guo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-29
Latest Update: 2026-01-29
Description:
Offers tools for data formatting, anomaly detection, and classification of tree-ring data using spatial comparisons and cross-correlation. Supports flexible detrending and climate–growth modeling via generalized additive mixed models (Wood 2017, ISBN:978-1498728331) and the 'mgcv' package (<https://CRAN.R-project.org/package=mgcv>), enabling robust analysis of non-linear trends and autocorrelated data. Provides standardized visual reporting, including summaries, diagnostics, and model performance. Compatible with '.rwl' files and tailored for the Canadian Forest Service Tree-Ring Data (CFS-TRenD) repository (Girardin et al. (2021) <doi:10.1139/er-2020-0099>), offering a comprehensive and adaptable framework for dendrochronologists working with large and complex datasets.
How to cite:
Xiao Jing Guo (2026). growthTrendR: Toolkit for Data Processing, Quality, and Statistical Models. R package version 0.2.2, https://cran.r-project.org/web/packages/growthTrendR. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:46), 0.2.0 (2026-01-24 12:00), 0.2.1 (2026-01-29 18:40)
Other packages that cited growthTrendR R package
View growthTrendR citation profile
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Complete documentation for growthTrendR
Functions, R codes and Examples using the growthTrendR R package
Full growthTrendR package functions and examples
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