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  "Title": "Ridge-Type Penalized Estimation of a Potpourri of Models",
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  "Date": "2024-02-21",
  "Author": "Wessel N. van Wieringen [aut, cre]\n(<https://orcid.org/0000-0002-5100-9123>), Mehran Aflakparast\n[ctb] (part of the R-code of the mixture functionality)",
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  "Description": "The name of the package is derived from the French, 'pour'\nridge, and provides functionality for ridge-type estimation of\na potpourri of models. Currently, this estimation concerns that\nof various Gaussian graphical models from different study\ndesigns. Among others it considers the regular Gaussian\ngraphical model and a mixture of such models. The\nporridge-package implements the estimation of the former either\nfrom i) data with replicated observations by penalized\nloglikelihood maximization using the regular ridge penalty on\nthe parameters (van Wieringen, Chen, 2021) or ii) from\nnon-replicated data by means of either a ridge estimator with\nmultiple shrinkage targets (as presented in van Wieringen et\nal. 2020, <doi:10.1016/j.jmva.2020.104621>) or the generalized\nridge estimator that allows for both the inclusion of\nquantitative and qualitative prior information on the precision\nmatrix via element-wise penalization and shrinkage (van\nWieringen, 2019, <doi:10.1080/10618600.2019.1604374>).\nAdditionally, the porridge-package facilitates the ridge\npenalized estimation of a mixture of Gaussian graphical models\n(Aflakparast et al., 2018). On another note, the package also\nincludes functionality for ridge-type estimation of the\ngeneralized linear model (as presented in van Wieringen,\nBinder, 2022, <doi:10.1080/10618600.2022.2035231>).",
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