{ "_id": "6a1edb43b401979e7340f7d4", "Package": "TrendLSW", "Type": "Package", "Title": "Wavelet Methods for Analysing Locally Stationary Time Series", "Version": "1.0.6", "Authors@R": "c(person(\"Euan T.\", \"McGonigle\", email=\"e.t.mcgonigle@soton.ac.uk\",role=c(\"aut\", \"cre\")),\nperson(\"Rebecca\",\"Killick\", role=\"aut\"),\nperson(\"Matthew\",\"Nunes\", role=\"aut\"))", "Maintainer": "Euan T. McGonigle ", "Description": "Fitting models for, and simulation of, trend locally\nstationary wavelet (TLSW) time series models, which take\naccount of time-varying trend and dependence structure in a\nunivariate time series. The TLSW model, and its estimation, is\ndescribed in McGonigle, Killick and Nunes (2022a)\n, (2022b) .\nFurther information regarding the use of the package, along\nwith detailed examples, can be found in McGonigle, Killick and\nNunes (2025) . New users will likely\nwant to start with the TLSW function.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "LazyData": "true", "URL": "https://github.com/EuanMcGonigle/TrendLSW", "BugReports": "https://github.com/EuanMcGonigle/TrendLSW/issues", "RoxygenNote": "7.3.2", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libglpk-dev libxml2-dev", "Repository": "https://euanmcgonigle.r-universe.dev", "Date/Publication": "2026-01-20 22:20:13 UTC", "RemoteUrl": "https://github.com/euanmcgonigle/trendlsw", "RemoteRef": "HEAD", "RemoteSha": "bc859f1434945bf14e986c7e4a9fd8563054ea83", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-20 08:53:41 UTC", "User": "root" }, "Author": "Euan T. 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