{ "_id": "6ac8c261de46216d5edd69f2", "Package": "DTWUMI", "Type": "Package", "Title": "Imputation of Multivariate Time Series Based on Dynamic Time\nWarping", "Version": "1.1", "Date": "2026-09-08", "Authors@R": "c( person(given=\"Camille\", family=\"Dezecache\", role = c(\"aut\")),\nperson(given=c(\"Thi\",\"Thu\", \"Hong\"), family=\"Phan\", role = c(\"aut\"),\nemail = \"hongptt11@fe.edu.vn\"),\nperson(given=\"Emilie\", family=\"Poisson-Caillault\", role = c(\"aut\", \"cre\"),\nemail = \"emilie.poisson@univ-littoral.fr\"))", "Description": "Functions to impute large gaps within multivariate time\nseries based on Dynamic Time Warping methods. Gaps of size 1 or\ninferior to a defined threshold are filled using simple average\nand weighted moving average respectively. Larger gaps are\nfilled using the methodology provided by Phan et al. (2017)\n: a query is built immediately\nbefore/after a gap and a moving window is used to find the most\nsimilar sequence to this query using Dynamic Time Warping. To\nlower the calculation time, similar sequences are pre-selected\nusing global features. Contrary to the univariate method\n(package 'DTWBI'), these global features are not estimated over\nthe sequence containing the gap(s), but a feature matrix is\nbuilt to summarize general features of the whole multivariate\nsignal. Once the most similar sequence to the query has been\nidentified, the adjacent sequence to this window is used to\nfill the gap considered. This function can deal with multiple\ngaps over all the sequences componing the input multivariate\nsignal. However, for better consistency, large gaps at the same\nlocation over all sequences should be avoided.", "License": "GPL (>= 2)", "URL": "https://mawenzi.univ-littoral.fr/DTWUMI/", "NeedsCompilation": "no", "Encoding": "UTF-8", "Packaged": { "Date": "2026-10-09 10:28:29 UTC", "User": "root" }, "Config/roxygen2/version": "8.1.0", "Author": "Camille Dezecache [aut], Thi Thu Hong Phan [aut], Emilie\nPoisson-Caillault [aut, cre]", "Maintainer": "Emilie Poisson-Caillault ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-09-09 08:40:08 UTC", "RemoteUrl": "https://github.com/cran/DTWUMI", "RemoteRef": "HEAD", "RemoteSha": "774d905e9a0fbf1f733ec2ed32fa065961fb9bbd", "_user": "cran", "_type": "src", "_file": "DTWUMI_1.1.tar.gz", "_fileid": "https://r2.ropensci.org/ccb25f798cbfac159deff076628fc1ac8a07ac22cf0eba38c26d151e43251b3a", "_filesize": 131114, "_sha256": "ccb25f798cbfac159deff076628fc1ac8a07ac22cf0eba38c26d151e43251b3a", "_expires": "2027-01-17T10:30:56.000Z", 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