Stochastic modeling of sunshine number data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F13%3A00398524" target="_blank" >RIV/67985807:_____/13:00398524 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1063/1.4832815" target="_blank" >http://dx.doi.org/10.1063/1.4832815</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/1.4832815" target="_blank" >10.1063/1.4832815</a>

Result language
angličtina
Original language name
Stochastic modeling of sunshine number data
Original language description
We present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and itwas shown to be useful both for theoretical and practical purposes, e.g. those related to the photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical modelfor SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact our logistic Markovian model can be fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of int
Czech name
—
Czech description
—

Project
<a href="/en/project/LD12009" target="_blank" >LD12009: Advanced methods for energy production forecasting by photovoltaic systems using high resolution NWP models</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)