Publication
Robust filtering with quantile regression
| dc.contributor.author | Assunção, João Borges | |
| dc.contributor.author | Fernandes, Pedro Afonso | |
| dc.date.accessioned | 2022-07-21T14:18:36Z | |
| dc.date.available | 2022-07-21T14:18:36Z | |
| dc.date.issued | 2022-02-21 | |
| dc.description.abstract | This working paper proposes a new, practical method to compute the non-linear Mosheiov-Raveh (MR) filter using least absolute deviations (LAD) instead of the linear programming approach proposed by these two authors. This paper is embodied with an implementation in the R programming language of the proposed method which facilitates the computation of the MR filter in current applications to produce a robust estimate, namely, of the GDP trend growth. This technique may be appropriate to deal with non linear time series or structural changes. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.14/38332 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Business cycles | pt_PT |
| dc.subject | Non linear time series | pt_PT |
| dc.subject | Robust filtering | pt_PT |
| dc.subject | Software | pt_PT |
| dc.title | Robust filtering with quantile regression | pt_PT |
| dc.type | working paper | |
| dspace.entity.type | Publication | |
| oaire.citation.title | Robust filtering with quantile regression | pt_PT |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | workingPaper | pt_PT |
Files
Original bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- NECEP_RP2_2022_Robust_Filtering_with_Quantile_Regression.pdf
- Size:
- 378.99 KB
- Format:
- Adobe Portable Document Format
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 3.44 KB
- Format:
- Item-specific license agreed upon to submission
- Description: