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  "Title": "Comprehensive Regime Change Detection in Time Series",
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  "Description": "A unified framework for detecting regime changes\n(changepoints) in time series data. Implements both frequentist\nmethods including Cumulative Sum (CUSUM, Page (1954)\n<doi:10.1093/biomet/41.1-2.100>), Pruned Exact Linear Time\n(PELT, Killick, Fearnhead, and Eckley (2012)\n<doi:10.1080/01621459.2012.737745>), Binary Segmentation, and\nWild Binary Segmentation, as well as Bayesian methods such as\nBayesian Online Changepoint Detection (BOCPD, Adams and MacKay\n(2007) <doi:10.48550/arXiv.0710.3742> and Shiryaev-Roberts.\nSupports offline analysis for retrospective detection and\nonline monitoring for real-time surveillance. Provides rigorous\nuncertainty quantification through confidence intervals and\nposterior distributions. Handles univariate and multivariate\nseries with detection of changes in mean, variance, trend, and\ndistributional properties.",
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        "RegimeChange"
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      "source": "bayesian-methods.Rmd",
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      "title": "Bayesian Changepoint Detection",
      "author": "José Mauricio Gómez Julián",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "BOCPD: Bayesian Online Changepoint Detection",
        "Prior Specification",
        "Normal-Gamma Prior",
        "Normal Prior with Known Variance",
        "Poisson-Gamma Prior",
        "Hazard Prior",
        "Geometric Hazard",
        "Constant Hazard",
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        "Probability of Change at Each Point",
        "Posterior Visualization",
        "Run Length Distribution",
        "Shiryaev-Roberts Procedure",
        "Uncertainty Quantification",
        "Credible Intervals",
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        "Online Mode",
        "Multivariate BOCPD",
        "Comparison: BOCPD vs Frequentist",
        "Advantages and Limitations",
        "Advantages",
        "Limitations",
        "Best Practices",
        "References"
      ],
      "created": "2026-04-07 12:47:36",
      "modified": "2026-04-07 12:47:36",
      "commits": 1
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      "filename": "introduction.html",
      "title": "Introduction to RegimeChange",
      "author": "José Mauricio Gómez Julián",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "Installation",
        "Quick Start",
        "Visualizing Results",
        "Available Methods",
        "Frequentist Methods",
        "Bayesian Methods",
        "Types of Changes",
        "Prior Specification (Bayesian Methods)",
        "Evaluation",
        "Method Comparison",
        "Online Detection",
        "Uncertainty Quantification",
        "Next Steps"
      ],
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      "modified": "2026-04-07 12:47:36",
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      "filename": "offline-detection.html",
      "title": "Offline Changepoint Detection",
      "author": "José Mauricio Gómez Julián",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "When to Use Offline Detection",
        "PELT: Pruned Exact Linear Time",
        "Penalty Selection",
        "Minimum Segment Length",
        "Binary Segmentation",
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