README.md

In jernejjevsenak/dendroLib: Library with Nonlinear Methods for Analyzing Dendroclimatological Data

dendroLib

The core purpose of the dendroLib package is to introduce novel dendroclimatological methods to study linear and nonlinear relationship between daily climate data and tree-ring sequences. The core function is daily_response, which finds the optimal sequence of days that are linearly or nonlinearly related to a tree-ring proxy records. . To use daily_response function, two data frames are required, one with daily climate data, e.g. temperatures; and one with tree-ring proxy records. Example data is provided, so users can see, how data frames should be organized. The daily_response function calculates all possible values of a selected statistical measure between response variables and daily environmental data. Calculations are based on a moving window, which runs through daily environmental data and calculates moving averages.

Installation

You can install dendroLib from github with:

# install.packages("devtools")
devtools::install_github("jernejjevsenak/dendroLib")

Examples

This is a basic example which shows you how to use the package:

## basic example code
library(dendroLib)
data(daily_temperatures_example) 
data(example_proxies_1)
result1 <- daily_response(response = example_proxies_1, env_data = daily_temperatures_example, 
                            method = "lm", measure = "r.squared", lower_limit = 90, upper_limit = 150)

This function is computationally intensive and it takes a while to calculate all possible values. Especially, if nonlinear "brnn" method is used. Each calculated value is printed, therefore user can be sure, that algorithm is still calculating. The return of this function is a list with three elements: @calculations, @method, @measure. The return is organized in a way, that can be used by three plotting functions: plot_extreme(), plot_specific() and plot_heatmap(). Function plot_extreme() graphs a line plot of a row with the highest calculated measure. It indicates the sequence of days, that are the most related to the response variable(s). With plot_specific(), measures with selected window width are plotted. Function plot_heatmap() is a visual representation of calculated values.

plot_extreme(result1, title = TRUE)

plot_specific(result1, window_width = 100, title = TRUE)

plot_heatmap(result1)

Authors

• Jernej Jevšenak

Collaborators

• Prof. dr. Tom Levanič

jernejjevsenak/dendroLib documentation built on May 12, 2019, 1:04 p.m.