Kernel Weighting for blending probability and non-probability survey samples Rueda García, María Del Mar Cobo Rodríguez, Beatriz Rueda-Sánchez, Jorge Luis Ferri García, Ramón Castro Martín, Luis Kernel weighting survey sampling non-probability sample coverage bias selection bias In this paper we review some methods proposed in the literature for combining a nonprobability and a probability sample with the purpose of obtaining an estimator with a smaller bias and standard error than the estimators that can be obtained using only the probability sample. We propose a new methodology based on the kernel weighting method. We discuss the properties of the new estimator when there is only selection bias and when there are both coverage and selection biases. We perform an extensive simulation study to better understand the behaviour of the proposed estimator. 2025-06-23T07:19:50Z 2025-06-23T07:19:50Z 2023 journal article • Rueda, María; Cobo, Beatriz; Rueda, Jorge Luis, Ferri, Ramón; Castro, Luis. Kernel Weighting for blending probability and non-probability survey samples. Statistics and Operations Research Transactions (SORT), 48(1), 93-124. 2023. (0.7, Q3). https://doi.org/10.57645/20.8080.02.15. 2/5 https://hdl.handle.net/10481/104746 10.57645/20.8080.02.15 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Inst Estadística Catalunya-Idescat