Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Forecasting of Self-Rated Health Using Hidden Markov Algorithm
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this thesis a model for predicting a person’s monthly average of self-rated health the following month was developed. It was based on statistics from a form constructed by HealthWatch. The model used is a Hidden Markov Algorithm based on Hidden Markov Models where the hidden part is the future value of self-rated health. The emissions were based on five of the eleven questions that make the HealthWatch form. The questions are answered on a scale from zero to one hundred. The model predicts in which of three intervals of SRH the responder most likely will answer on average during the following month. The final model has an accuracy of 80 %.

Place, publisher, year, edition, pages
2014.
Series
TRITA-MAT-E, 2014:17
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-142359OAI: oai:DiVA.org:kth-142359DiVA: diva2:705996
Subject / course
Mathematical Statistics
Educational program
Master of Science - Mathematics
Supervisors
Examiners
Available from: 2014-03-18 Created: 2014-02-28 Last updated: 2014-03-18Bibliographically approved

Open Access in DiVA

fulltext(362 kB)93 downloads
File information
File name FULLTEXT02.pdfFile size 362 kBChecksum SHA-512
158b96c3d41484b3e1a1d29faba41ffe8272224b0bb274d63d23aedb73a5c575079b90d4b0507e65c2dffd8fd512096eff0ff1d21bdec3ea3744448b846dcabc
Type fulltextMimetype application/pdf

By organisation
Mathematical Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 93 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 73 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf