Novo Díaz, SilviaAneiros, GermánVieu, Philippe2025-05-162025Novo, S., Aneiros, G. & Vieu, P. Semi-functional partial linear regression with measurement error: an approach based on kNN estimation. TEST 34, 235–261 (2025). https://doi.org/10.1007/s11749-024-00957-31133-0686http://hdl.handle.net/2183/42010This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11749-024-00957-3[Abstract]: This paper focuses on a semi-parametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the corresponding explanatory variable is measured with additive error and its dimension is finite (p). The other component models, in a nonparametric way, the effect of a functional variable (infinite dimension) on the response. kNN-based estimators are proposed for each component, and some asymptotic results are obtained. A simulation study illustrates the behaviour of such estimators for finite sample sizes, while an application to real data shows the usefulness of our proposal.engCopyright © 2024, The Author(s) under exclusive licence to Sociedad de Estadística e Investigación OperativaErrors-in-variablesFunctional datakNN estimationPartially linear modelsSemi-functional regressionjournal articleopen access10.1007/s11749-024-00957-3