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The asymptotic distribution of the mean estimator is derived, and asymptotic confidence bands are constructed. A comparative simulation study shows that free-knot splines estimate salient features of the functions (such as sharp peaks) more accurately than smoothing splines. This adaptive behaviour is also illustrated by an analysis of weather data.<\/jats:p>","DOI":"10.1111\/j.1467-9868.2006.00561.x","type":"journal-article","created":{"date-parts":[[2006,7,19]],"date-time":"2006-07-19T12:08:38Z","timestamp":1153310918000},"page":"671-687","source":"Crossref","is-referenced-by-count":26,"title":["Free-Knot Spline Smoothing for Functional Data"],"prefix":"10.1093","volume":"68","author":[{"given":"Daniel","family":"Gervini","sequence":"first","affiliation":[{"name":"University of Wisconsin\u2014Milwaukee , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2006,7,19]]},"reference":[{"key":"2023040800100685000_","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/BF01404567","article-title":"Smoothing noisy data with spline functions","volume":"31","author":"Craven","year":"1979","journal-title":"Numer. 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