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multispatialCCM (version 1.3)

Multispatial Convergent Cross Mapping

Description

The multispatial convergent cross mapping algorithm can be used as a test for causal associations between pairs of processes represented by time series. This is a combination of convergent cross mapping (CCM), described in Sugihara et al., 2012, Science, 338, 496-500, and dew-drop regression, described in Hsieh et al., 2008, American Naturalist, 171, 71–80. The algorithm allows CCM to be implemented on data that are not from a single long time series. Instead, data can come from many short time series, which are stitched together using bootstrapping.

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Version

Install

install.packages('multispatialCCM')

Monthly Downloads

320

Version

1.3

License

GPL (>= 2)

Maintainer

Last Published

October 22nd, 2023

Functions in multispatialCCM (1.3)

CCM_bootstrap

Run multispatial CCM algorithm on two time series
SSR_pred_boot

State space reconstruction function
make_ccm_data

Makes fake data for other functions
CCM_boot

Run multispatial CCM algorithm on two time series
SSR_check_signal

Test process for auto-predictability.
ccmtest

Test for significant causal signal
multispatialCCM-package

multispatial convergent cross mapping analysis