Listar Modelización, Optimización e Inferencia Estadística (MODES) por autor "Sperlich, Stefan"
Mostrando ítems 1-4 de 4
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Bandwidth Selection for Prediction in Regression
Barbeito, Inés; Cao, Ricardo; Sperlich, Stefan (M D P I AG, 2019-08-05)[Abstract] There exist many different methods to choose the bandwidth in kernel regression. If, however, the target is regression based prediction for samples or populations with potentially different distributions, then ... -
Bootstrap-based statistical inference for linear mixed effects under misspecifications
Reluga, Katarzyna; Lombardía, María José; Sperlich, Stefan (Elsevier, 2024)[Abstract]: Linear mixed effects are considered excellent predictors of cluster-level parameters in various domains. However, previous research has demonstrated that their performance is affected by departures from model ... -
Simultaneous Inference for Empirical Best Predictors With a Poverty Study in Small Areas
Reluga, Katarzyna; Lombardía, María José; Sperlich, Stefan (Taylor and Francis Group, 2023-01)[Abstract]: Today, generalized linear mixed models (GLMM) are broadly used in many fields. However, the development of tools for performing simultaneous inference has been largely neglected in this domain. A framework for ... -
Simultaneous inference for linear mixed model parameters with an application to small area estimation
Reluga, Katarzyna; Lombardía, María José; Sperlich, Stefan (John Wiley & Sons, 2022)[Abstract]: Over the past decades, linear mixed models have attracted considerable attention in various fields of applied statistics. They are popular whenever clustered, hierarchical or longitudinal data are investigated. ...