| 000 | 00000cam 2200000zi 4500 |
| 001 | 9.965211 |
| 003 | CaOODSP |
| 005 | 20260814145657 |
| 006 | m o d f |
| 007 | cr cn||||||||| |
| 008 | 260814e20260702oncd ob f000 0 eng d |
| 040 | |aCaOODSP|beng|erda|cCaOODSP |
| 086 | 1 |aFB3-5/2026-23E-PDF |
| 100 | 1 |aRodriguez Rondon, Gabriel, |eauthor. |
| 245 | 10|aMonte Carlo likelihood-ratio tests for Markov switching models / |cGabriel Rodriguez Rondon, Jean-Marie Dufour. |
| 264 | 1|a[Ottawa] : |bBank of Canada = Banque du Canada, |cJuly 2, 2026. |
| 264 | 4|c©2026 |
| 300 | |a1 online resource (34, A-23 pages) : |bgraphs. |
| 336 | |atext|btxt|2rdacontent |
| 337 | |acomputer|bc|2rdamedia |
| 338 | |aonline resource|bcr|2rdacarrier |
| 490 | 1 |aStaff working paper = |aDocument de travail du personnel, |x1701-9397 ; |v2026-23 |
| 500 | |aTitle from cover. |
| 504 | |aIncludes bibliographical references (pages 29-34, A-23). |
| 520 | 3 |a"Markov switching models are widely used to capture nonlinearities arising from regime shifts. Most existing tests for the number of regimes focus on one versus two regimes. Even in such simple cases, this type of problem raises issues of non-standard asymptotic distributions, identification failure, and nuisance parameters. We address these difficulties by applying the technique of Monte Carlo tests, which yields both finite-sample and asymptotically valid procedures, without the need to establish an asymptotic distributional theory, nor the existence of an asymptotic distribution"--Abstract. |
| 650 | 0|aHidden Markov models. |
| 650 | 0|aStatistical hypothesis testing. |
| 650 | 6|aModèles de Markov cachés. |
| 650 | 6|aTests d'hypothèses (Statistique) |
| 710 | 2 |aBank of Canada, |eissuing body. |
| 830 | #0|aStaff working paper (Bank of Canada)|x1701-9397 ; |v2026-23.|w(CaOODSP)9.806221 |
| 856 | 40|qPDF|s894 KB|uhttps://publications.gc.ca/collections/collection_2026/banque-bank-canada/FB3-5-2026-23-eng.pdf |