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  "Title": "Conjugate Power Priors for Bayesian Analysis of Normal Data",
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  "Description": "Implements conjugate power priors for efficient Bayesian\nanalysis of normal data. Power priors allow principled\nincorporation of historical information while controlling the\ndegree of borrowing through a discounting parameter (Ibrahim\nand Chen (2000) <doi:10.1214/ss/1009212519>). This package\nprovides closed-form conjugate representations for both\nunivariate and multivariate normal data using\nNormal-Inverse-Chi-squared and Normal-Inverse-Wishart\ndistributions, eliminating the need for MCMC sampling. The\nconjugate framework builds upon standard Bayesian methods\ndescribed in Gelman et al. (2013, ISBN:978-1439840955).",
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      "title": "Posterior Obtained by Updating Power Prior with Current Data (Multivariate)",
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      "title": "Posterior Obtained by Updating Power Prior with Current Data (Univariate)",
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      "title": "Compute Power Prior for Multivariate Normal Data",
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      "title": "Compute Power Prior for Univariate Normal Data",
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