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Selecting Single Model in Combination Forecasting Based on Cointegration Test and Encompassing Test
- Source :
- The Scientific World Journal, Vol 2014 (2014), The Scientific World Journal
- Publication Year :
- 2014
- Publisher :
- Hindawi Limited, 2014.
-
Abstract
- Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in the selection of single model, supplemented by empirical analysis, the paper gives the single model selection guidance: no more than five suitable single models can be selected from many alternative single models for a certain forecasting target, which increases accuracy and stability.
- Subjects :
- Article Subject
Computer science
Stability (learning theory)
lcsh:Medicine
Empirical Research
computer.software_genre
lcsh:Technology
General Biochemistry, Genetics and Molecular Biology
Empirical research
Statistics
lcsh:Science
Selection (genetic algorithm)
General Environmental Science
Single model
Cointegration
lcsh:T
lcsh:R
General Medicine
Function (mathematics)
Models, Theoretical
Test (assessment)
lcsh:Q
Probabilistic forecasting
Data mining
computer
Research Article
Forecasting
Subjects
Details
- Language :
- English
- ISSN :
- 23566140
- Volume :
- 2014
- Database :
- OpenAIRE
- Journal :
- The Scientific World Journal
- Accession number :
- edsair.doi.dedup.....ca5a746c7379328fa11358f19fcadc54