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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
TRITA-MAT-E, 2014:17
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-142359OAI: diva2:705996
Subject / course
Mathematical Statistics
Educational program
Master of Science - Mathematics
Available from: 2014-03-18 Created: 2014-02-28 Last updated: 2014-03-18Bibliographically approved

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