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==Markov-chain forecasting models==
Markov-chains have been used as a forecasting methods for several topics, for example price trends,<ref name="SLS">{{cite journal |first1=E.G. |last1=de Souza e Silva |first2=L.F.L. |last2=Legey |first3=E.A. |last3=de Souza e Silva |url=https://www.sciencedirect.com/science/article/pii/S0140988310001271 |title=Forecasting oil price trends using wavelets and hidden Markov models |journal=Energy Economics |volume=32 |year=2010|issue=6 |page=1507 |doi=10.1016/j.eneco.2010.08.006 |bibcode=2010EneEc..32.1507D }}</ref> wind power<ref name="CGLT">{{cite journal |first1=A |last1=Carpinone |first2=M |last2=Giorgio |first3=R. |last3=Langella |first4=A. |last4=Testa |title=Markov chain modeling for very-short-term wind power forecasting |journal=Electric Power Systems Research |volume=122 |pages=152–158 |year=2015|doi=10.1016/j.epsr.2014.12.025 |doi-access=free |bibcode=2015EPSR..122..152C }}</ref> and [[solar irradiance]].<ref name="MMW">{{cite journal |first1=J. |last1=Munkhammar |first2=D.W. |last2=van der Meer |first3=J. |last3=Widén |title=Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model |journal= Solar Energy |volume=184 |pages=688–695 |year=2019|doi=10.1016/j.solener.2019.04.014 |bibcode=2019SoEn..184..688M |s2cid=146076100 }}</ref> The Markov-chain forecasting models utilize a variety of different settings, from discretizing the time-series<ref name="CGLT" /> to hidden Markov-models combined with wavelets<ref name="SLS" /> and the Markov-chain mixture distribution model (MCM).<ref name="MMW" />
== See also ==
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