{
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  "Title": "Robust Hotelling-Type T² Control Chart Based on the Dual STATIS\nApproach",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(\"Sergio Daniel\", \"Frutos Galarza\", , \"sergio_dan88@hotmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0007-2961-032X\")),\nperson(\"Omar\", \"Ruiz Barzola\", , \"oruiz@espol.edu.ec\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-8206-1744\")),\nperson(\"Purificación\", \"Galindo Villardón\", , \"pgalindo@usal.es\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-6977-7545\"))\n)",
  "Description": "Implements a robust multivariate control-chart methodology\nfor batch-based industrial processes with multiple correlated\nvariables using the Dual STATIS (Structuration des Tableaux A\nTrois Indices de la Statistique) framework. A robust compromise\ncovariance matrix is constructed from Phase I batches with the\nMinimum Covariance Determinant (MCD) estimator, and a\nHotelling-type T² statistic is applied for anomaly detection in\nPhase II. The package includes functions to simulate clean and\ncontaminated batches, to compute both robust and classical\nHotelling T² control charts, to visualize results via robust\nbiplots, and to launch an interactive 'shiny' dashboard. An\ninternal dataset (pharma_data) is provided for reproducibility.\nSee Lavit, Escoufier, Sabatier and Traissac (1994)\n<doi:10.1016/0167-9473(94)90134-1> for the original STATIS\nmethodology, and Rousseeuw and Van Driessen (1999)\n<doi:10.1080/00401706.1999.10485670> for the MCD estimator.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/SergioDanielFG/robustT2",
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  "Language": "en-US",
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  "Date/Publication": "2025-09-05 15:46:36 UTC",
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  "Author": "Sergio Daniel Frutos Galarza [aut, cre] (ORCID:\n<https://orcid.org/0009-0007-2961-032X>),\nOmar Ruiz Barzola [aut] (ORCID:\n<https://orcid.org/0000-0001-8206-1744>),\nPurificación Galindo Villardón [aut] (ORCID:\n<https://orcid.org/0000-0001-6977-7545>)",
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