Matches in SemOpenAlex for { <https://semopenalex.org/work/W3201442046> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W3201442046 abstract "Confidence intervals are a standard technique for analyzing data. When applied to time series, confidence intervals are computed for each time point separately. Alternatively, we can compute confidence bands, where we are required to find the smallest area enveloping k time series, where k is a user parameter. Confidence bands can be then used to detect abnormal time series, not just individual observations within the time series. We will show that despite being an NP-hard problem it is possible to find optimal confidence band for some k. We do this by considering a different problem: discovering regularized bands, where we minimize the envelope area minus the number of included time series weighted by a parameter (alpha ). Unlike normal confidence bands we can solve the problem exactly by using a minimum cut. By varying (alpha ) we can obtain solutions for various k. If we have a constraint k for which we cannot find appropriate (alpha ), we demonstrate a simple algorithm that yields ( mathcal {O} mathopen {}left( sqrt{n}right) ) approximation guarantee by connecting the problem to a minimum k-union problem. This connection also implies that we cannot approximate the problem better than ( mathcal {O} mathopen {}left( n^{1/4}right) ) under some (mild) assumptions. Finally, we consider a variant where instead of minimizing the area we minimize the maximum width. Here, we demonstrate a simple 2-approximation algorithm and show that we cannot achieve better approximation guarantee." @default.
- W3201442046 created "2021-09-27" @default.
- W3201442046 creator A5067444605 @default.
- W3201442046 date "2021-01-01" @default.
- W3201442046 modified "2023-09-25" @default.
- W3201442046 title "Approximation Algorithms for Confidence Bands for Time Series" @default.
- W3201442046 cites W1535144194 @default.
- W3201442046 cites W167817876 @default.
- W3201442046 cites W1983383464 @default.
- W3201442046 cites W2035575256 @default.
- W3201442046 cites W2044113250 @default.
- W3201442046 cites W2054788982 @default.
- W3201442046 cites W2109532231 @default.
- W3201442046 cites W2144399314 @default.
- W3201442046 cites W2162800060 @default.
- W3201442046 cites W2266714125 @default.
- W3201442046 cites W2950509221 @default.
- W3201442046 cites W2963725737 @default.
- W3201442046 cites W3118621910 @default.
- W3201442046 cites W3121632873 @default.
- W3201442046 doi "https://doi.org/10.1007/978-3-030-86486-6_27" @default.
- W3201442046 hasPublicationYear "2021" @default.
- W3201442046 type Work @default.
- W3201442046 sameAs 3201442046 @default.
- W3201442046 citedByCount "0" @default.
- W3201442046 crossrefType "book-chapter" @default.
- W3201442046 hasAuthorship W3201442046A5067444605 @default.
- W3201442046 hasBestOaLocation W32014420462 @default.
- W3201442046 hasConcept C105795698 @default.
- W3201442046 hasConcept C111472728 @default.
- W3201442046 hasConcept C11413529 @default.
- W3201442046 hasConcept C114614502 @default.
- W3201442046 hasConcept C138885662 @default.
- W3201442046 hasConcept C143724316 @default.
- W3201442046 hasConcept C148764684 @default.
- W3201442046 hasConcept C151730666 @default.
- W3201442046 hasConcept C2524010 @default.
- W3201442046 hasConcept C2776036281 @default.
- W3201442046 hasConcept C2780586882 @default.
- W3201442046 hasConcept C28719098 @default.
- W3201442046 hasConcept C33923547 @default.
- W3201442046 hasConcept C41008148 @default.
- W3201442046 hasConcept C44249647 @default.
- W3201442046 hasConcept C86803240 @default.
- W3201442046 hasConceptScore W3201442046C105795698 @default.
- W3201442046 hasConceptScore W3201442046C111472728 @default.
- W3201442046 hasConceptScore W3201442046C11413529 @default.
- W3201442046 hasConceptScore W3201442046C114614502 @default.
- W3201442046 hasConceptScore W3201442046C138885662 @default.
- W3201442046 hasConceptScore W3201442046C143724316 @default.
- W3201442046 hasConceptScore W3201442046C148764684 @default.
- W3201442046 hasConceptScore W3201442046C151730666 @default.
- W3201442046 hasConceptScore W3201442046C2524010 @default.
- W3201442046 hasConceptScore W3201442046C2776036281 @default.
- W3201442046 hasConceptScore W3201442046C2780586882 @default.
- W3201442046 hasConceptScore W3201442046C28719098 @default.
- W3201442046 hasConceptScore W3201442046C33923547 @default.
- W3201442046 hasConceptScore W3201442046C41008148 @default.
- W3201442046 hasConceptScore W3201442046C44249647 @default.
- W3201442046 hasConceptScore W3201442046C86803240 @default.
- W3201442046 hasLocation W32014420461 @default.
- W3201442046 hasLocation W32014420462 @default.
- W3201442046 hasOpenAccess W3201442046 @default.
- W3201442046 hasPrimaryLocation W32014420461 @default.
- W3201442046 hasRelatedWork W10229777 @default.
- W3201442046 hasRelatedWork W10242137 @default.
- W3201442046 hasRelatedWork W10708998 @default.
- W3201442046 hasRelatedWork W10919197 @default.
- W3201442046 hasRelatedWork W2745897 @default.
- W3201442046 hasRelatedWork W2906494 @default.
- W3201442046 hasRelatedWork W3640231 @default.
- W3201442046 hasRelatedWork W3872339 @default.
- W3201442046 hasRelatedWork W6543118 @default.
- W3201442046 hasRelatedWork W11356929 @default.
- W3201442046 isParatext "false" @default.
- W3201442046 isRetracted "false" @default.
- W3201442046 magId "3201442046" @default.
- W3201442046 workType "book-chapter" @default.