dendroTools - Linear and Nonlinear Methods for Analyzing Daily and Monthly Dendroclimatological Data

Provides novel dendroclimatological methods, primarily used by the Tree-ring research community. There are four core functions. The first one is daily_response(), which finds the optimal sequence of days that are related to one or more tree-ring proxy records. Similar function is daily_response_seascorr(), which implements partial correlations in the analysis of daily response functions. For the enthusiast of monthly data, there is monthly_response() function. The last core function is compare_methods(), which effectively compares several linear and nonlinear regression algorithms on the task of climate reconstruction.

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6.60 score 7 stars 94 scripts 439 downloads

MLFS - Machine Learning Forest Simulator

Climate-sensitive, single-tree forest simulator based on data-driven machine learning. It simulates the main forest processes— radial growth, height growth, mortality, crown recession, regeneration, and harvesting—so users can assess stand development under climate and management scenarios. The height model is described by Skudnik and Jevšenak (2022) <doi:10.1016/j.foreco.2022.120017>, the basal-area increment model by Jevšenak and Skudnik (2021) <doi:10.1016/j.foreco.2020.118601>, and an overview of the MLFS package, workflow, and applications is provided by Jevšenak, Arnič, Krajnc, and Skudnik (2023), Ecological Informatics <doi:10.1016/j.ecoinf.2023.102115>.

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3.90 score 2 stars 40 scripts 536 downloads

rTG - Methods to Analyse Seasonal Radial Tree Growth Data

Methods for comparing different regression algorithms for describing the temporal dynamics of secondary tree growth (xylem and phloem). Users can compare the accuracy of the most common fitting methods usually used to analyse xylem and phloem data, i.e., Gompertz function, Double Gompertz function, General Additive Models (GAMs); and an algorithm newly introduced to the field, i.e., Bayesian Regularised Neural Networks (brnn). The core function of the package is XPSgrowth(), while the results can be interpreted using implemented generic S3 methods, such as plot() and summary().

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2.74 score 1 stars 11 scripts 240 downloads