Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wildi, Marc | - |
| dc.date.accessioned | 2019-04-24T10:09:22Z | - |
| dc.date.available | 2019-04-24T10:09:22Z | - |
| dc.date.issued | 1999 | - |
| dc.identifier.isbn | 978-3-540-65381-3 | de_CH |
| dc.identifier.isbn | 978-3-642-58409-1 | de_CH |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/16836 | - |
| dc.description.abstract | Traditionally, trend-estimation or -extraction methods for non-stationary time series (ARIMA-model based, structural models, Census X12,…) make use of a stochastic modeling procedure which not only determines an optimal symmetric MA(∞)-extraction filter (this is not true for Census XI2) but also supplies missing values at both ends of a finite sample by optimal fore- and backcasts, hence minimizing the unconditional final revision variance. In this paper we propose a new trend estimation procedure based on a direct filtering approach. We generalize the class of time invariant filters by including explicit time dependence towards the end of a sample and optimizing in each time point a corresponding filter with respect to a conditional final revision variance minimization. The condition corresponds to a time delay restriction and this will generalize usual unconditional optimization procedures. It is shown that this optimization underlies an uncertainty-principle (APUP) which is best solved by general IIR- or ARMA-filters instead of the usual MA-designs. This direct IIR-filter-method may be used either for traditional trend extraction or for detection of compatible turning-points of a series (to be defined below). In the latter case it is shown that the theoretical extraction filter has a transferfunction taking the form of an indicator function. | de_CH |
| dc.language.iso | en | de_CH |
| dc.publisher | Springer | de_CH |
| dc.relation.ispartofseries | Operations Research Proceedings | de_CH |
| dc.rights | Licence according to publishing contract | de_CH |
| dc.subject.ddc | 510: Mathematik | de_CH |
| dc.title | Detection of compatible turning-points and signal-extraction of non-stationary time series | de_CH |
| dc.type | Konferenz: Paper | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | School of Engineering | de_CH |
| zhaw.organisationalunit | Institut für Datenanalyse und Prozessdesign (IDP) | de_CH |
| zhaw.publisher.place | Heidelberg | de_CH |
| dc.identifier.doi | 10.1007/978-3-642-58409-1_29 | de_CH |
| zhaw.conference.details | International Conference on Operations Research, Zurich, 31 August - 3 September 1998 | de_CH |
| zhaw.funding.eu | No | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.pages.end | 299 | de_CH |
| zhaw.pages.start | 293 | de_CH |
| zhaw.publication.status | publishedVersion | de_CH |
| zhaw.series.number | 1998 | de_CH |
| zhaw.publication.review | Peer review (Abstract) | de_CH |
| zhaw.title.proceedings | Operations Research Proceedings 1998 | de_CH |
| Appears in collections: | Publikationen School of Engineering | |
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Wildi, M. (1999). Detection of compatible turning-points and signal-extraction of non-stationary time series [Conference paper]. Operations Research Proceedings 1998, 293–299. https://doi.org/10.1007/978-3-642-58409-1_29
Wildi, M. (1999) ‘Detection of compatible turning-points and signal-extraction of non-stationary time series’, in Operations Research Proceedings 1998. Heidelberg: Springer, pp. 293–299. Available at: https://doi.org/10.1007/978-3-642-58409-1_29.
M. Wildi, “Detection of compatible turning-points and signal-extraction of non-stationary time series,” in Operations Research Proceedings 1998, 1999, pp. 293–299. doi: 10.1007/978-3-642-58409-1_29.
WILDI, Marc, 1999. Detection of compatible turning-points and signal-extraction of non-stationary time series. In: Operations Research Proceedings 1998. Conference paper. Heidelberg: Springer. 1999. S. 293–299. ISBN 978-3-540-65381-3
Wildi, Marc. 1999. “Detection of Compatible Turning-Points and Signal-Extraction of Non-Stationary Time Series.” Conference paper. In Operations Research Proceedings 1998, 293–99. Heidelberg: Springer. https://doi.org/10.1007/978-3-642-58409-1_29.
Wildi, Marc. “Detection of Compatible Turning-Points and Signal-Extraction of Non-Stationary Time Series.” Operations Research Proceedings 1998, Springer, 1999, pp. 293–99, https://doi.org/10.1007/978-3-642-58409-1_29.
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