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| 001 | 293784 | ||
| 003 | MX-SnUAN | ||
| 005 | 20160429155120.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150903s2005 gw | o |||| 0|eng d | ||
| 020 |
_a9783540269168 _99783540269168 |
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| 024 | 7 |
_a10.1007/b138291 _2doi |
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| 035 | _avtls000346774 | ||
| 039 | 9 |
_a201509031100 _bVLOAD _c201405070511 _dVLOAD _y201402070905 _zstaff |
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| 040 |
_aMX-SnUAN _bspa _cMX-SnUAN _erda |
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| 050 | 4 | _aQA276-280 | |
| 100 | 1 |
_aWildi, Marc. _eautor _9326736 |
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| 245 | 1 | 0 |
_aSignal Extraction : _bEfficient Estimation, ‘Unit Root'-Tests and Early Detection of Turning Points / _cby Marc Wildi. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2005. |
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| 300 |
_axI, 279 páginas 80 ilustraciones _brecurso en línea. |
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| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_acomputadora _bc _2rdamedia |
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| 338 |
_arecurso en línea _bcr _2rdacarrier |
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| 347 |
_aarchivo de texto _bPDF _2rda |
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| 490 | 0 |
_aLecture Notes in Economics and Mathematical Systems, _x0075-8442 ; _v547 |
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| 500 | _aSpringer eBooks | ||
| 505 | 0 | _aTheory -- Model-Based Approaches -- QMP-ZPC Filters -- The Periodogram -- Direct Filter Approach (DFA) -- Finite Sample Problems and Regularity -- Empirical Results -- Empirical Comparisons : Mean Square Performance -- Empirical Comparisons : Turning Point Detection -- Conclusion. | |
| 520 | _aThe book provides deep insights into the signal extraction problem - especially at the boundary of a sample, where asymmetric filters must be used - and how to solve it optimally. The traditional model-based approach (TRAMO/SEATS or X-12-ARIMA) is an inefficient estimation method because it relies on one-step ahead forecasting performances (of a model) whereas the signal extraction problem implicitly requires good multi-step ahead forecasts also. Unit roots are important properties of the input signal because they generate a set of constraints for the best extraction filter. Since traditional tests essentially rely on one-step ahead forecasting performances, new tests are presented here which implicitly account for multi-step ahead forecasting performances too. The gain in efficiency obtained by the new estimation method is analyzed in great detail, using simulated data as well as 'real world' time series. | ||
| 590 | _aPara consulta fuera de la UANL se requiere clave de acceso remoto. | ||
| 710 | 2 |
_aSpringerLink (Servicio en línea) _9299170 |
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| 776 | 0 | 8 |
_iEdición impresa: _z9783540229353 |
| 856 | 4 | 0 |
_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b138291 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL) |
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