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| 001 | 9.949546 |
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| 003 | CaOODSP |
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| 005 | 20250326115127 |
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| 006 | m o d f |
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| 007 | cr |n||||||||| |
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| 008 | 250326t20242024oncd ob f|0| 0 eng d |
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| 040 | |aCaOODSP|beng|erda|cCaOODSP |
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| 041 | |aeng|beng|bfre |
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| 043 | |an-cn--- |
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| 086 | 1 |aFB3-6/2024-17E-PDF |
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| 100 | 1 |aMollins, Jeff, |eauthor. |
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| 245 | 10|aSeasonal adjustment of weekly data / |cby Jeffrey Mollins and Rachit Lumb. |
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| 264 | 1|a[Ottawa] : |bBank of Canada = Banque du Canada, |c2024. |
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| 264 | 4|c©2024 |
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| 300 | |a1 online resource (ii, 21 pages) : |bcharts. |
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| 336 | |atext|btxt|2rdacontent |
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| 337 | |acomputer|bc|2rdamedia |
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| 338 | |aonline resource|bcr|2rdacarrier |
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| 490 | 1 |aStaff discussion paper = |lDocument d'analyse du personnel, |y1914-0568 ; |v2024-17 |
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| 500 | |a"Last updated: November 18, 2024." |
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| 500 | |aISSN assigned to different series. |
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| 504 | |aIncludes bibliographical references. |
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| 520 | |a"This paper summarizes and assesses several of the most popular methods to seasonally adjust weekly data. The industry standard approach, known as X-13ARIMA-SEATS, is suitable only for monthly or quarterly data. Given the increased availability and promise of non-traditional data at higher frequencies, alternative approaches are required to extract relevant signals for monitoring and analysis. This paper reviews four such methods for high-frequency seasonal adjustment"--Abstract, page ii. |
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| 546 | |aIncludes abstract in French. |
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| 650 | 0|aEconometric models|zCanada. |
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| 650 | 6|aModèles économétriques|zCanada. |
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| 710 | 2 |aBank of Canada, |eissuing body. |
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| 830 | #0|aStaff discussion paper (Bank of Canada)|v2024-17.|w(CaOODSP)9.806273 |
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| 856 | 40|qPDF|s719 KB|uhttps://publications.gc.ca/collections/collection_2025/banque-bank-canada/FB3-6-2024-17-eng.pdf |
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