In jernejjevsenak/dendroTools: Linear and Nonlinear Methods for Analyzing Daily and Monthly Dendroclimatological Data

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dendroTools

The core purpose of the dendroTools package is to introduce novel dendroclimatological methods to study linear and nonlinear relationships between environmental (climate) data and tree-ring sequences in R. The two functions, which are used to study climate-growth relationships using daily climate data, are daily_response() and daily_response_seascorr(), while the two functions for monthly data are monthly_response() and monthly_response_seascorr(). The seascorr functions are designed to study partial correlation coefficients, while the other two can be used to calculate simple correlations, or fit linear and nonlinear models between aggregated climate data and tree-ring proxies. To use daily_response(), two data frames are required, one with daily climate data, e.g. mean daily temperature; and one with tree-ring proxy records. Example data is provided, so users can see, how data frames should be organized. The daily_response() calculates all possible values of a selected statistical metric between response variable(s) and daily environmental data. Calculations are based on a moving window, which runs through daily environmental data and calculates moving averages. In addition, there generic functions are available for visualization and interpretation of results.
A completely separate function is the compare_methods() which can be used to compare different regression methods for climate reconstruction. It calculates several performance metrics for train and test data for different regression methods: multiple linear regression (MLR), artificial neural networks with Bayesian regularization training algorithm (BRNN), M5P model trees (MT), model trees with bagging (BMT) and random forest of regression trees (RF). Calculated performance metrics are correlation coefficient (r), root mean squared error (RMSE), root relative squared error (RRSE), index of agreement (d), reduction of error (RE), coefficient of efficiency (CE) and mean bias.

Installation

You can install dendroTools using:

library("devtools")
devtools::install_github("jernejjevsenak/dendroTools") # current version under development

install.packages("dendroTools") # from CRAN

Authors

• Jernej Jevšenak

jernejjevsenak/dendroTools documentation built on April 23, 2024, 6:01 p.m.