> For the complete documentation index, see [llms.txt](https://time-series-features.gitbook.io/pyspi/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://time-series-features.gitbook.io/pyspi/information-about-pyspi/spis/spi-descriptions.md).

# SPI Descriptions

Descriptions of each method.

{% hint style="info" %}
The documentation accompanying the toolkit, including the tables and descriptions of each SPI, represent the features and functionality of the original pyspi library as detailed in the [Supplementary Material ](https://www.readcube.com/articles/supplement?doi=10.1038%2Fs43588-023-00519-x\&index=0)of the original *pyspi* paper. While we strive to keep our documentation as current and comprehensive as possible, our library of SPIs may undergo frequent updates and enhancements to align with the latest advancements and user feedback.
{% endhint %}

## Basic Statistics

<table data-view="cards"><thead><tr><th align="center"></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"></td><td align="center"><strong>Covariance</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/basic-statistics.md#basic-spis-overview">Basic Statistics</a></td></tr><tr><td align="center"></td><td align="center"><p><strong>Cross</strong></p><p><strong>Correlation</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/basic-statistics.md#covariance-estimators">Basic Statistics</a></td></tr><tr><td align="center"></td><td align="center"><strong>Kendall's Rank Correlation Coefficient</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/basic-statistics.md#cross-correlation-estimators">Basic Statistics</a></td></tr><tr><td align="center"></td><td align="center"><strong>Precision</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/basic-statistics.md#kendalls-rank-correlation-coefficient-estimator">Basic Statistics</a></td></tr><tr><td align="center"></td><td align="center"><strong>Spearman's Rank Correlation Coefficient</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/basic-statistics.md#precision-estimators">Basic Statistics</a></td></tr></tbody></table>

***

## Distance Similarity

<table data-view="cards"><thead><tr><th></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td align="center"><strong>Barycenter</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#distance-similarity-spis-overview">Distance Similarity</a></td></tr><tr><td></td><td align="center"><p><strong>Cross Distance</strong></p><p><strong>Correlation</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#barycenter-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Cross Multiscale Graph Correlation</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#cross-distance-correlation-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Distance Correlation</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#cross-multiscale-graph-correlation-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><p><strong>Dynamic Time</strong></p><p><strong>Warping</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#distance-correlation-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Gromov-Wasserstein Distance</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#dynamic-time-warping-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Heller-Heller-Gorfine Independence Criterion</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#dynamic-time-warping-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Hilbert-Schmidt Independence Criterion</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#heller-heller-gorfine-independence-criterion-estimator">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Longest Common Subsequence</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#hilbert-schmidt-independence-criterion-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Multiscale Graph Correlation</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#longest-common-subsequence-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Pairwise Distance</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#pairwise-distance-estimators">Distance Similarity</a></td></tr><tr><td></td><td align="center"><strong>Soft Dynamic Time Warping</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/distance-similarity.md#multiscale-graph-correlation-estimator">Distance Similarity</a></td></tr></tbody></table>

***

## Causal Inference

<table data-view="cards"><thead><tr><th></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td align="center"><strong>Additive Noise Model</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/causal-inference.md#causal-inference-spis-overview">Causal Inference</a></td></tr><tr><td></td><td align="center"><strong>Conditional Distribution Similarity Fit</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/causal-inference.md#additive-noise-estimator">Causal Inference</a></td></tr><tr><td></td><td align="center"><p><strong>Convergent</strong></p><p><strong>Cross-Mapping</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/causal-inference.md#conditional-distribution-similarity-fit-estimator">Causal Inference</a></td></tr><tr><td></td><td align="center"><strong>Information-Geometric Causal Inference</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/causal-inference.md#convergent-cross-mapping-estimators">Causal Inference</a></td></tr><tr><td></td><td align="center"><strong>Regression Error-Based Causal Inference</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/causal-inference.md#information-geometric-causal-inference-estimator">Causal Inference</a></td></tr></tbody></table>

***

## Information Theory

<table data-view="cards"><thead><tr><th></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td align="center"><strong>Causally Conditioned Entropy</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#information-theoretic-spis-overview">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Conditional Entropy</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#causally-conditioned-entropy-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Directed Information</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#conditional-entropy-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Granger Causality</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#directed-information-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Integrated Information</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#granger-causality-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Joint Entropy</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#integrated-information-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Mutual Information</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#joint-entropy-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Stochastic Interaction</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#mutual-information-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Transfer Entropy</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#stochastic-interaction-estimators">Information Theory</a></td></tr><tr><td></td><td align="center"><strong>Time-lagged Mutual Information</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/information-theory.md#transfer-entropy-estimators">Information Theory</a></td></tr></tbody></table>

***

## Spectral

<table data-view="cards"><thead><tr><th></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td align="center"><strong>Coherence Magnitude</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#spectral-spis-overview">Spectral</a></td></tr><tr><td></td><td align="center"><strong>Coherence Phase</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#coherence-magnitude-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Directed</strong></p><p><strong>Coherence</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#coherence-phase-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Directed Transfer</strong></p><p><strong>Function</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#directed-coherence-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><strong>Group Delay</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#directed-transfer-function-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><strong>Imaginary Coherence</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#group-delay-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><strong>Pairwise Phase Consistency</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#imaginary-coherence-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Partial Directed</strong></p><p><strong>Coherence</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#pairwise-phase-consistency-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Phase Lag</strong></p><p><strong>Index</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#partial-directed-coherence-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Phase Locking</strong></p><p><strong>Value</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#phase-lag-index-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Phase Slope</strong></p><p><strong>Index</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#phase-locking-value-estimators">Spectral</a></td></tr><tr><td></td><td align="center"><p><strong>Spectral Granger</strong></p><p><strong>Causality</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/spectral.md#phase-slop-index-estimators">Spectral</a></td></tr></tbody></table>

***

## Miscellaneous

<table data-view="cards"><thead><tr><th></th><th align="center"></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td></td><td align="center"><strong>Cointegration</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/miscellaneous.md#miscellaneous-spis-overview">Miscellaneous</a></td></tr><tr><td></td><td align="center"><p><strong>Gaussian Process</strong></p><p><strong>Model Fit</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/miscellaneous.md#cointegration-estimators">Miscellaneous</a></td></tr><tr><td></td><td align="center"><strong>Linear Model Fit</strong></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/miscellaneous.md#gaussian-process-model-fit-1">Miscellaneous</a></td></tr><tr><td></td><td align="center"><p><strong>Power Envelope</strong></p><p><strong>Correlation</strong></p></td><td></td><td><a href="/pyspi/information-about-pyspi/spis/spi-descriptions/miscellaneous.md#linear-model-fit-estimators">Miscellaneous</a></td></tr></tbody></table>

***


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