Statistical Models for Disaggregation and Reaggregation of Natural Gas Consumption Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00436216" target="_blank" >RIV/67985807:_____/15:00436216 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/15:10285455
Result on the web
<a href="http://dx.doi.org/10.1080/02664763.2014.993365" target="_blank" >http://dx.doi.org/10.1080/02664763.2014.993365</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/02664763.2014.993365" target="_blank" >10.1080/02664763.2014.993365</a>
Alternative languages
Result language
angličtina
Original language name
Statistical Models for Disaggregation and Reaggregation of Natural Gas Consumption Data
Original language description
In this paper, we present a unified framework for natural gas consumption modeling and forecasting. This consists of models of GAM class and their nonlinear extension, tailored for easy estimation, aggregation and treatment of the delayed relationship between temperature and consumption. Since the consumption data for households and small commercial customers are routinely available in many countries only as long-term sum meter readings, their disaggregation and possibly reaggregation to different timeintervals is necessary for a variety of purposes. We show some examples of specific models based on the presented framework and then we demonstrate their use in practice, especially for the disaggregation and reaggregation tasks.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Applied Statistics
ISSN
0266-4763
e-ISSN
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Volume of the periodical
42
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
17
Pages from-to
921-937
UT code for WoS article
000349904500001
EID of the result in the Scopus database
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