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  "Title": "Fit Penalised Generalised Least Squares models",
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  "Description": "Combine generalised least squares methodology from the\nnlme package for dealing with autocorrelation with penalised\nleast squares methods from the glmnet package to deal with high\ndimensionality. This pengls packages glues them together\nthrough an iterative loop. The resulting method is applicable\nto high dimensional datasets that exhibit autocorrelation, such\nas spatial or temporal data.",
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  "Encoding": "UTF-8",
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  "biocViews": "Transcriptomics, Regression, TimeCourse, Spatial",
  "BugReports": "https://github.com/sthawinke/pengls/issues",
  "URL": "https://github.com/sthawinke/pengls",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:57:28 UTC",
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      "page": "coef.cv.pengls",
      "title": "Extract coefficients from a cv.pengls model",
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