DC FieldValueLanguage
dc.contributor.authorWeiß, Christian H.-
dc.date.accessioned2020-04-23T14:47:20Z-
dc.date.available2020-04-23T14:47:20Z-
dc.date.issued2018-
dc.identifier.citationEnthalten in: Wiley StatsRef, April 2014-. - 2018, insges. 8 S.de_DE
dc.description.abstractCategorical time series are discretevalued time series having a qualitative range, which consists of a finite number of categories. As standard methods from realvalued time series analysis cannot be applied to such a kind of data, tailormade tools for the visualization of the time series, characterizing the marginal distribution and measuring serial dependence are presented. Also, common stochastic models for such time series are surveyed, including types of Markov models, discrete ARMA models, HiddenMarkov models, and regression models.de_DE
dc.description.sponsorshipQuantitative Methoden der Wirtschaftswissenschaftende_DE
dc.language.isoende_DE
dc.relation.ispartofWiley StatsRefde_DE
dc.titleCategorical Time Series Analysisde_DE
dc.typeArticlede_DE
dc.identifier.doi10.1002/9781118445112.stat08132-
dcterms.bibliographicCitation.volume2018de_DE
dc.relation.pagesinsges. 8 S.de_DE
dc.identifier.urlhttps://ub.hsu-hh.de/DB=1.8/XMLPRS=N/PPN?PPN=1031846956-
local.submission.typeonly-metadatade_DE
item.languageiso639-1en-
item.fulltext_sNo Fulltext-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.grantfulltextnone-
crisitem.author.deptQuantitative Methoden der Wirtschaftswissenschaften-
crisitem.author.parentorgFakultät für Wirtschafts- und Sozialwissenschaften-
Appears in Collections:2018
Show simple item record

CORE Recommender

Google ScholarTM

Check

Altmetric

Altmetric


Items in openHSU are protected by copyright, with all rights reserved, unless otherwise indicated.