{ "_id": "6ac6c608ca1b382b34ef440c", "Package": "aersn", "Type": "Package", "Title": "Affine-Equivariant Adjusted-Range Self-Normalization for\nTime-Series Inference", "Version": "0.2.3", "Authors@R": "c(\nperson(\"Yongmiao\", \"Hong\", role = \"aut\"),\nperson(\"Zhuo\", \"Lin\", role = \"aut\"),\nperson(\"Oliver\", \"Linton\", role = \"aut\"),\nperson(c(\"Whitney\", \"K.\"), \"Newey\", role = \"aut\"),\nperson(\"Jiajing\", \"Sun\", email = \"jiajing.sun@gmail.com\",\nrole = c(\"aut\", \"cre\")))", "Description": "Tuning-free inference on fixed-dimensional parameters of\ndependent time series using affine-equivariant adjusted-range\nself-normalization. The centered partial-sum path of estimated\ninfluence contributions is normalized by its increment hull,\nthe convex hull of all path increments. The gauge of the hull\nprovides an asymptotically pivotal test statistic and an\naffine-equivariant confidence region without estimating the\nlong-run covariance matrix, and its support function gives\nsimultaneous confidence intervals for linear contrasts. For a\nsingle parameter the construction reduces exactly to\nadjusted-range self-normalization, whose limiting distribution\nis available in closed form. The Brownian reference law is\nsimulated on a grid matched to the sample size or a supplied\ncommon variance-accumulation profile; inference for dependent\nobservations remains asymptotic. Five further methods are\nprovided for comparison on the same estimate and influence\ncontributions: componentwise adjusted ranges after lag-zero\npartial prewhitening, quadratic self-normalization following\nShao (2010) , kernel\nlong-run covariance estimation with automatic bandwidth\nselection following Andrews (1991) and\nNewey and West (1994) , Bartlett fixed-b\ninference following Kiefer and Vogelsang (2005)\n, and the equal-weighted cosine\nmethod of Lazarus, Lewis, Stock and Watson (2018)\n. Model interfaces are\nprovided for sample means, linear regression, smooth\ngeneralized method of moments, and conditional likelihood\nscores; other estimators are handled through user-supplied\ninfluence contributions. The methods follow Hong, Lin, Linton,\nNewey and Sun (2026), Cambridge Working Papers in Economics No.\n2678\n\nand, for the scalar case, Hong, Linton, McCabe, Sun and Wang\n(2024) .", "License": "MIT + file LICENSE", "URL": "https://www.janeway.econ.cam.ac.uk/publication/affine-equivariant-adjusted-range-self-normalization", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "LazyData": "true", "Config/roxygen2/version": "8.1.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-07 22:18:04 UTC", "User": "root" }, "Author": "Yongmiao Hong [aut], Zhuo Lin [aut], Oliver Linton [aut],\nWhitney K. 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