Package: patterncausality 0.2.4

Stavros Stavroglou

patterncausality: Pattern Causality Algorithm

A comprehensive package for detecting and analyzing causal relationships in complex systems using pattern-based approaches. Key features include state space reconstruction, pattern identification, and causality strength evaluation.

Authors:Stavros Stavroglou [aut, cre], Athanasios Pantelous [aut], Hui Wang [aut]

patterncausality_0.2.4.tar.gz
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patterncausality_0.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
patterncausality/json (API)

# Install 'patterncausality' in R:
install.packages('patterncausality', repos = c('https://pattern-causality.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pattern-causality/pattern_causality/issues

Datasets:

On CRAN:

Conda:

5.69 score 6 stars 27 scripts 432 downloads 19 exports 38 dependencies

Last updated from:9763e09418. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK168
source / vignettesOK300
linux-release-x86_64OK186
macos-release-arm64OK226
macos-oldrel-arm64OK169
windows-develOK104
windows-releaseOK113
windows-oldrelOK111
wasm-releaseOK138

Exports:distanceMetricoptimalParametersSearchpc_cvpc_effectpc_matrixpc_paramspcAccuracypcCrossMatrixpcCrossValidationpcEffectpcFullDetailspcLightweightpcMatrixplot_causalityplot_componentsplot_totalstateSpacestateSpaceMethodvalidate_custom_fn_output

Dependencies:clicpp11dplyrfarvergenericsggplot2ggrepelggthemesgluegridExtragtableisobandlabelinglifecyclemagrittrmisc3dpillarpkgconfigplot3DplyrpurrrR6RColorBrewerRcppreshape2rlangS7scalesstatebinsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Exploring Pattern Causality: An Intuitive Guide
Application in Financial Markets | Parameter Optimization | Calculating Causality | Detailed Analysis | Parameter Description
Rendered frompatterncausality.Rmdusingknitr::rmarkdown

Last update: 2025-02-15
Started: 2024-08-02

Unveiling Causal Relationships in Time Series Data
Cross-Validation: Ensuring the Reliability of Causal Inference | Cross-Validation: Convergence of Pattern Causality | Cross-Validation with Bootstrap Analysis
Rendered fromseries.Rmdusingknitr::rmarkdown

Last update: 2025-01-10
Started: 2024-08-24

Parallel Computing in Pattern Causality Analysis
Key Benefits of Parallel Computing | Performance Comparison: Sequential vs Parallel Computing | Create test data | Function to measure execution time | Compare sequential vs parallel | Matrix Analysis with Multiple Time Series | Understanding Parallel Performance | Key Factors Affecting Speed-up | Best Practices for Optimal Performance | System-Specific Considerations | Windows Systems | Linux/Mac Systems | Memory Usage Guidelines | Conclusion
Rendered fromparallel.Rmdusingknitr::rmarkdown

Last update: 2025-01-04
Started: 2025-01-03

Multiple Series Pattern Causality Analysis: Unveiling System-Wide Interactions
Pattern Causality Matrix | Pattern Causality Effect | Cross Matrix analysis
Rendered frommatrix.Rmdusingknitr::rmarkdown

Last update: 2024-12-17
Started: 2024-08-24

Advanced Pattern Causality: Custom Functions for Tailored Analysis
Custom Distance Metric | Custom State Space Reconstruction | Applying Custom Functions | Comparing Results
Rendered fromadvanced.Rmdusingknitr::rmarkdown

Last update: 2024-12-16
Started: 2024-12-16

Dynamic Analysis: Pattern Causality in Time Points
Causality Strength Analysis with ERF Function | Raw Causality Strength Analysis
Rendered fromdynamic.Rmdusingknitr::rmarkdown

Last update: 2024-12-16
Started: 2024-12-16

Readme and manuals

Help Manual

Help pageTopics
Illapel Ecological DatasetAUCO
Climate Indices Datasetclimate_indices
Distance Metric InterfacedistanceMetric distanceMetric.custom distanceMetric.default
Dow Jones Stock Price DatasetDJS
Search for Optimal Parameters in Pattern Causality AnalysisoptimalParametersSearch
Pattern Causality Cross-Validation Objectpc_cv
Pattern Causality Effect Objectpc_effect
Pattern Causality Matrix Objectpc_matrix
Pattern Causality Parameter Optimization Resultspc_params
Calculate Pattern Causality AccuracypcAccuracy
Cross Pattern Causality Matrix AnalysispcCrossMatrix
Pattern Causality Cross-Validation AnalysispcCrossValidation
Pattern Causality Effect AnalysispcEffect
Calculate Full Details Pattern Causality AnalysispcFullDetails
Calculate Pattern Causality Using Lightweight AlgorithmpcLightweight
Pattern Causality Matrix AnalysispcMatrix
Plot Pattern Causality Time Seriesplot_causality
Plot Pattern Causality Time Seriesplot_causality.pc_full_details
Plot Pattern Causality Componentsplot_components
Plot Causality Componentsplot_components.pc_fit
Plot Total Pattern Causalityplot_total
Plot Total Causalityplot_total.pc_fit
Plot Pattern Causality Cross Validation Resultsplot.pc_cv
Plot Pattern Causality Effectplot.pc_effect
Plot Pattern Causality Resultsplot.pc_fit
Plot Pattern Causality Matrixplot.pc_matrix
Plot State Space Reconstructionplot.pc_state
Print Method for Pattern Causality Accuracy Resultsprint.pc_accuracy
Print Pattern Causality Cross Validation Resultsprint.pc_cv
Print Pattern Causality Effectprint.pc_effect
Print Pattern Causality Resultsprint.pc_fit
Print Pattern Causality Matrixprint.pc_matrix
Print Method for Pattern Causality Parameter Resultsprint.pc_params
Print State Space Reconstructionprint.pc_state
Print Method for Pattern Causality Accuracy Summaryprint.summary.pc_accuracy
State Space ReconstructionstateSpace
State Space Reconstruction InterfacestateSpaceMethod stateSpaceMethod.custom stateSpaceMethod.default
Summary Method for Pattern Causality Accuracy Resultssummary.pc_accuracy
Summary of Pattern Causality Cross Validation Resultssummary.pc_cv
Summarize Pattern Causality Effectsummary.pc_effect
Summarize Pattern Causality Resultssummary.pc_fit
Summarize Pattern Causality Matrixsummary.pc_matrix
Summary Method for Pattern Causality Parameter Resultssummary.pc_params
Summarize State Space Reconstructionsummary.pc_state
Validate Custom Function Output for Pattern Causality Analysisvalidate_custom_fn_output