Matches in SemOpenAlex for { <https://semopenalex.org/work/W2053189280> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W2053189280 endingPage "93" @default.
- W2053189280 startingPage "75" @default.
- W2053189280 abstract "This paper explores recursive prediction and likelihood evaluation techniques for periodic autoregressive moving‐average (PARMA) time series models. The innovations algorithm is used to develop a simple recursive scheme for computing one‐step‐ahead predictors and their mean squared errors. The asymptotic form of this recursion is explored. The prediction results are then used to develop an efficient (and exact) PARMA likelihood evaluation algorithm for Gaussian series. We then show how a multivariate autoregressive moving average (ARMA) likelihood can be evaluated by writing the multivariate ARMA model in PARMA form. Explicit calculations for PARMA(1, 1) models and periodic autoregressions are included." @default.
- W2053189280 created "2016-06-24" @default.
- W2053189280 creator A5006419852 @default.
- W2053189280 creator A5032580070 @default.
- W2053189280 date "2000-01-01" @default.
- W2053189280 modified "2023-10-03" @default.
- W2053189280 title "Recursive Prediction and Likelihood Evaluation for Periodic ARMA Models" @default.
- W2053189280 doi "https://doi.org/10.1111/1467-9892.00174" @default.
- W2053189280 hasPublicationYear "2000" @default.
- W2053189280 type Work @default.
- W2053189280 sameAs 2053189280 @default.
- W2053189280 citedByCount "95" @default.
- W2053189280 countsByYear W20531892802012 @default.
- W2053189280 countsByYear W20531892802014 @default.
- W2053189280 countsByYear W20531892802015 @default.
- W2053189280 countsByYear W20531892802016 @default.
- W2053189280 countsByYear W20531892802017 @default.
- W2053189280 countsByYear W20531892802018 @default.
- W2053189280 countsByYear W20531892802019 @default.
- W2053189280 countsByYear W20531892802020 @default.
- W2053189280 countsByYear W20531892802021 @default.
- W2053189280 countsByYear W20531892802022 @default.
- W2053189280 countsByYear W20531892802023 @default.
- W2053189280 crossrefType "journal-article" @default.
- W2053189280 hasAuthorship W2053189280A5006419852 @default.
- W2053189280 hasAuthorship W2053189280A5032580070 @default.
- W2053189280 hasConcept C105795698 @default.
- W2053189280 hasConcept C11413529 @default.
- W2053189280 hasConcept C121332964 @default.
- W2053189280 hasConcept C143724316 @default.
- W2053189280 hasConcept C151406439 @default.
- W2053189280 hasConcept C151730666 @default.
- W2053189280 hasConcept C155380588 @default.
- W2053189280 hasConcept C159877910 @default.
- W2053189280 hasConcept C161584116 @default.
- W2053189280 hasConcept C163716315 @default.
- W2053189280 hasConcept C168773036 @default.
- W2053189280 hasConcept C175706884 @default.
- W2053189280 hasConcept C24338571 @default.
- W2053189280 hasConcept C28826006 @default.
- W2053189280 hasConcept C33923547 @default.
- W2053189280 hasConcept C62520636 @default.
- W2053189280 hasConcept C74883015 @default.
- W2053189280 hasConcept C86803240 @default.
- W2053189280 hasConceptScore W2053189280C105795698 @default.
- W2053189280 hasConceptScore W2053189280C11413529 @default.
- W2053189280 hasConceptScore W2053189280C121332964 @default.
- W2053189280 hasConceptScore W2053189280C143724316 @default.
- W2053189280 hasConceptScore W2053189280C151406439 @default.
- W2053189280 hasConceptScore W2053189280C151730666 @default.
- W2053189280 hasConceptScore W2053189280C155380588 @default.
- W2053189280 hasConceptScore W2053189280C159877910 @default.
- W2053189280 hasConceptScore W2053189280C161584116 @default.
- W2053189280 hasConceptScore W2053189280C163716315 @default.
- W2053189280 hasConceptScore W2053189280C168773036 @default.
- W2053189280 hasConceptScore W2053189280C175706884 @default.
- W2053189280 hasConceptScore W2053189280C24338571 @default.
- W2053189280 hasConceptScore W2053189280C28826006 @default.
- W2053189280 hasConceptScore W2053189280C33923547 @default.
- W2053189280 hasConceptScore W2053189280C62520636 @default.
- W2053189280 hasConceptScore W2053189280C74883015 @default.
- W2053189280 hasConceptScore W2053189280C86803240 @default.
- W2053189280 hasIssue "1" @default.
- W2053189280 hasLocation W20531892801 @default.
- W2053189280 hasOpenAccess W2053189280 @default.
- W2053189280 hasPrimaryLocation W20531892801 @default.
- W2053189280 hasRelatedWork W1562203027 @default.
- W2053189280 hasRelatedWork W2061377831 @default.
- W2053189280 hasRelatedWork W2085582903 @default.
- W2053189280 hasRelatedWork W2746349969 @default.
- W2053189280 hasRelatedWork W3035565291 @default.
- W2053189280 hasRelatedWork W3115491726 @default.
- W2053189280 hasRelatedWork W3201591169 @default.
- W2053189280 hasRelatedWork W4205312218 @default.
- W2053189280 hasRelatedWork W4235728994 @default.
- W2053189280 hasRelatedWork W4385388092 @default.
- W2053189280 hasVolume "21" @default.
- W2053189280 isParatext "false" @default.
- W2053189280 isRetracted "false" @default.
- W2053189280 magId "2053189280" @default.
- W2053189280 workType "article" @default.