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BINCOR (version 0.2.1)

Estimate the Correlation Between Two Irregular Time Series

Description

Estimate the correlation between two irregular time series that are not necessarily sampled on identical time points. This program is also applicable to the situation of two evenly spaced time series that are not on the same time grid. 'BINCOR' is based on a novel estimation approach proposed by Mudelsee (2010, 2014) to estimate the correlation between two climate time series with different timescales. The idea is that autocorrelation (AR1 process) allows to correlate values obtained on different time points. 'BINCOR' contains four functions: bin_cor() (the main function to build the binned time series), plot_ts() (to plot and compare the irregular and binned time series, cor_ts() (to estimate the correlation between the binned time series) and ccf_ts() (to estimate the cross-correlation between the binned time series). A description of the method and package is provided in Polanco-Martínez et al. (2019), .

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Install

install.packages('BINCOR')

Monthly Downloads

276

Version

0.2.1

License

GPL (>= 2)

Maintainer

Josue Polanco-Martinez

Last Published

February 24th, 2026

Functions in BINCOR (0.2.1)

BINCOR-package

Estimate the Correlation Between Two Irregular Time Series
bin_cor

Binned correlation
ENSO.dat

Equatorial Pacific SST anomalies from El Niño 3 region.
NHSST.dat

Northern Hemisphere (NH) sea surface temperature (SST) anomalies.
redfitMinls

Minimization - least square
plot_ts

Plot time series
ID32.dat

Unevenly-spaced pollen record from the marine sediments core (MD95-2039) collected on the southwestern European margin.
ID31.dat

Unevenly-spaced pollen record from the marine sediments core (MD04-2845) collected on the southwestern European margin.
cor_ts

Bi-variate correlation
redfitTauest

Tauest
ccf_ts

Cross-correlation