Direct versus iterated multi-step forecasting of glycaemia in type 1 diabetics using autoregressive models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11130%2F20%3A10416579" target="_blank" >RIV/00216208:11130/20:10416579 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21460/20:00344983 RIV/68407700:21730/20:00344983 RIV/00064203:_____/20:10416579
Result on the web
<a href="https://doi.org/10.3233/SHTI200630" target="_blank" >https://doi.org/10.3233/SHTI200630</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/SHTI200630" target="_blank" >10.3233/SHTI200630</a>
Alternative languages
Result language
angličtina
Original language name
Direct versus iterated multi-step forecasting of glycaemia in type 1 diabetics using autoregressive models
Original language description
The paper compares two approaches to multi-step ahead glycaemia forecasting. While the direct approach uses a different model for each number of steps ahead, the iterative approach applies one one-step ahead model iteratively. Although it is well known that the iterative approach suffers from the error accumulation problem, there are no clear outcomes supporting a proper choice between those two methods. This paper provides such comparison for different ARX models and shows that the iterative approach outperformed the direct method for one-hour ahead (12-steps ahead) forecasting. Moreover, the classical linear ARX model outperformed more complex non-linear versions for training data covering one-month period.
Czech name
—
Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
30202 - Endocrinology and metabolism (including diabetes, hormones)
Result continuities
Project
<a href="/en/project/NV15-25710A" target="_blank" >NV15-25710A: Individual dynamics of glycaemia excursions identification in diabetic patients to improve self managing procedures influencing insulin dosage</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Studies in Health Technology and Informatics
ISBN
978-1-64368-112-2
ISSN
0926-9630
e-ISSN
—
Number of pages
6
Pages from-to
149-154
Publisher name
IOS Press BV
Place of publication
Amsterdam
Event location
Praha
Event date
Sep 14, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000648601600017