@misc{Kadiri_Nadia_Single_2023,
 author={Kadiri, Nadia and Mekki, Sanaà Dounya and Rabhi, Abbes},
 identifier={DOI 10.15611/eada.2023.3.01},
 year={2023},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Econometrics = Ekonometria, 2023, Vol. 27, No. 3, s. 1-19},
 language={eng},
 abstract={The primary goal of this research was to estimate the quantile of a conditional distribution using a semi-parametric approach in the presence of randomly missing data, where the predictor variable belongs to a semi-metric space. The authors assumed a single index structure to link the explanatory and response variable. First, a kernel estimator was proposed for the conditional distribution function, assuming that the data were selected from a stationary process with missing data at random (MAR). By imposing certain general conditions, the study established the model’s uniform almost complete consistencies with convergence rates.},
 title={Single Functional Index Quantile Regression for Functional Data with Missing Data at Random},
 type={artykuł},
 keywords={functional data analysis, funcional single index process, kernel estimator, missing at random, nonparametric estimation, small ball probability, funkcjonalna analiza danych, funkcjonalny proces pojedynczego indeksu, estymator jądra, losowe braki, estymacja nieparametryczna, prawdopodobieństwo małej kuli},
}