A comparative study of new cross-validated bandwidth selectors for kernel density estimation

Autor: Mammen, Enno, Miranda, Maria Dolores Martinez, Nielsen, Jens Perch, Sperlich, Stefan

Recent contributions to kernel smoothing show that the performance of cross-validated bandwidth selectors improve significantly from indirectness. Indirect crossvalidation first estimates the classical cross-validated bandwidth from a more rough and

Externí odkaz: http://arxiv.org/abs/1209.4495

Inference and forecasting in the age–period–cohort model with unknown exposure with an application to mesothelioma mortality

Autor: Miranda, María Dolores Martínez, Nielsen, Bent, Nielsen, Jens Perch

Publikováno v: Journal of the Royal Statistical Society. Series A (Statistics in Society), 2015 Jan 01. 178(1), 29-55.

Externí odkaz: http://www.jstor.org/stable/43965716

Global Polynomial Kernel Hazard Estimation:Ajuste polinomial global para la estimación kernel de la función de riesgo

Autor: Hiabu, Munir, Miranda, Maria Dolores Martínez, Nielsen, Jens Perch, Spreeuw, Jaap, Tanggaard, Carsten, Villegas, Andrés

Publikováno v: Hiabu, M, Miranda, M D M, Nielsen, J P, Spreeuw, J, Tanggaard, C & Villegas, A 2015, ' Global Polynomial Kernel Hazard Estimation : Ajuste polinomial global para la estimación kernel de la función de riesgo ', Revista Colombiana de Estadistica, vol. 38, no. 2, pp. 399-411 . https://doi.org/10.15446/rce.v38n2.51668

This paper introduces a new bias reducing method for kernel hazard estimation.The method is called global polynomial adjustment (GPA). It isa global correction which is applicable to any kernel hazard estimator. Theestimator works well from a theoret

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8da48928c805accb7505a7b73f06677c
https://pure.au.dk/ws/files/108984126/Global_Polynomial_Kernel_Hazard_Estimation_final_version_2015.pdf

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.