honeycomb_climate

<p>Monthly temperature and rainfall between 2009 and 2019 in 72 hexagonal cells covering The Americas.</p>

datasets

Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.

Blas M. Benito

distantia

Advanced Toolset for Efficient Time Series Dissimilarity
Analysis

honeycomb_climate function

<p>An object of class <code>tbl_df</code> (inherits from <code>tbl</code>, <code>data.frame</code>) with 9432 rows and 4 columns.</p>

honeycomb_climate: Rainfall and Temperature in The Americas

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See Also