@misc{Horabik-Pyzel_Joanna_Techniki_2013,
 author={Horabik-Pyzel, Joanna},
 copyright={Licencja Creative Commons Uznanie autorstwa 4.0},
 address={Warszawa},
 journal={Książka = Book},
 howpublished={online},
 year={2013},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={The purpose of this study is to develop a method for allocating pollutant concentrations to finer spatial scales conditional on covariate information observable in a fine grid. Spatial dependence is modeled with the conditional autoregressive structure. The maximum likelihood approach to inference is employed, and the optimal predictors are developed to assess missing concentrations in a fine grid. The method is developed for a practical application of an output from the dispersion model CALPUFF run for Warsaw agglomeration.},
 type={Tekst},
 title={Techniki informacyjne teoria i zastosowania * Wybrane problemy * Spatial disaggregation of air pollution data with conditional autoagressive model},
 URL={http://www.rcin.org.pl/Content/217804/PDF/KS-2013-05-15-P03.pdf},
}