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  "Maintainer": "Mark van der Loo <mark.vanderloo@gmail.com>",
  "License": "GPL-3",
  "Title": "Simple Imputation",
  "Type": "Package",
  "LazyLoad": "yes",
  "Authors@R": "c( person(\"Mark\", \"van der Loo\",\nrole=c(\"aut\",\"cre\"),email=\"mark.vanderloo@gmail.com\"))",
  "Description": "Easy to use interfaces to a number of imputation methods\nthat fit in the not-a-pipe operator of the 'magrittr' package.",
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  "URL": "https://github.com/markvanderloo/simputation",
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  "Date/Publication": "2024-08-02 12:08:54 UTC",
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  "_commit": {
    "id": "38965ad0857716182050a446d8416c9e47280569",
    "author": "Reijer Idema <151732163+reijeridema@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Fix predictive mean matching imputation. (#42)\n\n* Fix predictive mean matching for linear predictors.\r\n\r\nThe old implementation of predictive mean matching imputed based on the\r\ndistance between the donor values and the predicted target. However, the\r\nmethod is supposed to impute based on the distance between predicted\r\ndonor values and predicted target.\r\n\r\nThis change implements the correct behaviour for predictive mean\r\nmatching using linear predictors (impute_lm, impute_rlm and impute_en).\r\nIt also stops execution with an error if any other imputation function\r\nis passed as a predictor for impute_pmm().\r\n\r\n* Fix issues with donor selection in impute_pmm().\r\n\r\nThere were two issues with donor selection:\r\n- Donors with NA predictions were allowed in the donor pool, which could\r\n  lead to break-down in extreme cases without valid donors.\r\n- For the multivariate option, records in which values had been imputed\r\n  in earlier iterations were excluded from the donor pool, even if the\r\n  imputations were only in columns irrelevant to the current iteration.\r\n\r\nThis change fixes these issues and adds tests.\r\n\r\n* Use gower::topn() instead of C routine in univariate PMM.\r\n\r\nMultivariate PMM was already using gower::topn() to find the best donor\r\nvalues. There have been no reports of performance issues, and there is\r\nno reason to assume that performance will not suffice for the univariate\r\ncase as well. This change slightly simplifies the package.\r\n\r\n* Add impute_all option to impute_cart() and impute_rf().\r\n\r\nWith this change, tree models can be used as predictor in impute_pmm().\r\n\r\n* Improve impute_pmm() to handle imputed data with 0 range.\r\n\r\nIf the range is 0, gower_topn() cannot calculate the closest donor. We\r\ncatch this case and pick the first eligible donor, which is consistent\r\nwith the behaviour for gower_topn() in case of equal donor values.\r\n\r\n* Update NEWS file.\r\n\r\n---------\r\n\r\nCo-authored-by: Reijer Idema <r.idema@cbs.nl>",
    "time": 1722600534
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  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "data-science",
    "imputation",
    "officialstatistics"
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