Combining Sequence Analysis and Hidden Markov Models in the Analysis of Complex Life Sequence Data

Tietueen suppeat tiedot
dc.contributor.authorSatu Helske
dc.contributor.authorJouni Helske
dc.contributor.authorMervi Eerola
dc.contributor.organizationfi=INVEST tutkimuskeskus ja lippulaiva|en=INVEST Research Flagship Centre|
dc.contributor.organizationfi=sosiologia|en=Sociology|
dc.contributor.organizationfi=tilastotiede|en=Statistics|
dc.contributor.organization-code1.2.246.10.2458963.20.11531668876
dc.contributor.organization-code1.2.246.10.2458963.20.42133013740
dc.contributor.organization-code2603303
dc.converis.publication-id36281787
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/36281787
dc.date.accessioned2025-08-28T00:49:56Z
dc.date.available2025-08-28T00:49:56Z
dc.description.abstract<p>Life course data often consists of multiple parallel sequences, one for each life domain of interest. Multichannel sequence analysis has been used for computing pairwise dissimilarities and finding clusters in this type of multichannel (or multidimensional) sequence data. Describing and visualizing such data is, however, often challenging. We propose an approach for compressing, interpreting, and visualizing the information within multichannel sequences by finding (1) groups of similar trajectories and (2) similar phases within trajectories belonging to the same group. For these tasks we combine multichannel sequence analysis and hidden Markov modelling. We illustrate this approach with an empirical application to life course data but the proposed approach can be useful in various longitudinal problems.</p>
dc.format.pagerange185
dc.format.pagerange200
dc.identifier.isbn978-3-319-95419-6
dc.identifier.issn2211-7776
dc.identifier.olddbid206497
dc.identifier.oldhandle10024/189524
dc.identifier.urihttps://www.utupub.fi/handle/11111/46850
dc.identifier.urnURN:NBN:fi-fe2021042719958
dc.language.isoen
dc.okm.affiliatedauthorEerola, Mervi
dc.okm.affiliatedauthorHelske, Satu
dc.okm.affiliatedauthorHelske, Jouni
dc.okm.discipline112 Statistics and probabilityen_GB
dc.okm.discipline5141 Sociologyen_GB
dc.okm.discipline515 Psychologyen_GB
dc.okm.discipline112 Tilastotiedefi_FI
dc.okm.discipline5141 Sosiologiafi_FI
dc.okm.discipline515 Psykologiafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA3 Book
dc.publisherSpringer
dc.publisher.isbn978-81-322;978-3-540;978-3-642;978-3-662;978-3-7908;978-3-8274;978-3-8347;978-90-481;978-94-007;978-94-009;978-94-010;978-94-011;978-94-015;978-94-017;978-94-024;978-0-387;978-0-8176;978-1-4419;978-1-4612;978-1-4613;978-1-4614;978-1-4615;978-1-4684;978-1-4757;978-1-4899;978-1-4939;978-1-5041;978-3-319;978-1-4020;978-0-85729;978-1-4471;978-1-84628;978-1-84800;978-1-84882;978-1-84996;978-1-85233;978-3-211;978-3-7091;978-4-431;978-3-322;978-3-409;978-3-531;978-3-658;978-3-663;978-3-8100;978-981-287;978-981-10;978-981-13;978-3-030;978-981-32;978-981-15;978-981-16;978-981-329;978-981-334;978-981-336;978-3-031;978-981-19;
dc.relation.doi10.1007/978-3-319-95420-2
dc.relation.ispartofseriesLife Course Research and Social Policies
dc.relation.volume10
dc.source.identifierhttps://www.utupub.fi/handle/10024/189524
dc.titleCombining Sequence Analysis and Hidden Markov Models in the Analysis of Complex Life Sequence Data
dc.title.bookSequence Analysis and Related Approaches
dc.year.issued2018

Tiedostot

Näytetään 1 - 1 / 1
Name:
Helske2018_Chapter_CombiningSequenceAnalysisAndHi.pdf
Size:
664.95 KB
Format:
Adobe Portable Document Format
Description:
Publisher's version
Lataa

Kokoelmat

Rinnakkaistallenteet