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  "Description": "A tool for multiply imputing missing data using 'MIDAS', a\ndeep learning method based on denoising autoencoder neural\nnetworks (see Lall and Robinson, 2022;\n<doi:10.1017/pan.2020.49>). This algorithm offers significant\naccuracy and efficiency advantages over other multiple\nimputation strategies, particularly when applied to large\ndatasets with complex features. Alongside interfacing with\n'Python' to run the core algorithm, this package contains\nfunctions for processing data before and after model training,\nrunning imputation model diagnostics, generating multiple\ncompleted datasets, and estimating regression models on these\ndatasets. For more information see Lall and Robinson (2023)\n<doi:10.18637/jss.v107.i09>. This package is deprecated in\nfavor of 'rMIDAS2'; it remains available for existing workflows\nbut will receive only compatibility and documentation updates.",
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        "rMIDAS"
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      "title": "Reverse numeric conversion of binary vector",
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