{ "_id": "6a104858acfb0bcc41c9f2d2", "Type": "Package", "Package": "rjd3filters", "Title": "Trend-Cycle Extraction with Linear Filters based on JDemetra+\nv3.x", "Version": "2.3.0", "Authors@R": "c(\nperson(\"Jean\", \"Palate\", , \"palatejean@gmail.com\", role = \"aut\"),\nperson(\"Alain\", \"Quartier-la-Tente\", , \"alain.quartier@yahoo.fr\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-7890-3857\")),\nperson(\"Tanguy\", \"Barthelemy\", , \"tanguy.barthelemy@insee.fr\", role = \"ctb\"),\nperson(\"Anna\", \"Smyk\", , \"anna.smyk@insee.fr\", role = \"ctb\")\n)", "Description": "This package provides functions to build and apply\nsymmetric and asymmetric moving averages (= linear filters) for\ntrend-cycle extraction. In particular, it implements several\nmodern approaches for real-time estimates from the viewpoint of\nrevisions and time delay in detecting turning points. It\nincludes the local polynomial approach of Proietti and Luati\n(2008), the Reproducing Kernel Hilbert Space (RKHS) of Dagum\nand Bianconcini (2008) and the Fidelity-Smoothness-Timeliness\napproach of Grun-Rehomme, Guggemos, and Ladiray (2018). 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