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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.
| Version: | 1.3 |
| Depends: | R (≥ 3.0.2) |
| Published: | 2023-10-22 |
| Author: | Adam Clark |
| Maintainer: | Adam Clark <adam.tclark at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| CRAN checks: | multispatialCCM results |
| Reference manual: | multispatialCCM.pdf |
| Package source: | multispatialCCM_1.3.tar.gz |
| Windows binaries: | r-devel: multispatialCCM_1.3.zip, r-release: multispatialCCM_1.3.zip, r-oldrel: multispatialCCM_1.3.zip |
| macOS binaries: | r-release (arm64): multispatialCCM_1.3.tgz, r-oldrel (arm64): multispatialCCM_1.3.tgz, r-release (x86_64): multispatialCCM_1.3.tgz, r-oldrel (x86_64): multispatialCCM_1.3.tgz |
| Old sources: | multispatialCCM archive |
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These binaries (installable software) and packages are in development.
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