Wszystkie pola: nonparametric estimation - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Nonparametric bootstrap confidence bands for unfolding sphere size distributions
Autorzy:: Wojdyła, Jakub
Powiązania:: https://bibliotekanauki.pl/articles/2049017.pdf
Data publikacji:: 2021
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: bootstrap
confidence bands
inverse problem
nonparametric density estimation
Wicksell’s problem
Opis:: The stereological inverse problem of unfolding the distribution of spheres radii from measured planar sections radii, known as the Wicksell’s corpuscle problem, is considered. The construction of uniform confidence bands based on the smoothed bootstrap in the Wicksell’s problem is presented. Theoretical results on the consistency of the proposed bootstrap procedure are given, where the consistency of the bands means that the coverage probability converges to the nominal level. The finite-sample performance of the proposed method is studied via Monte Carlo simulations and compared with the asymptotic (non-bootstrap) solution described in literature.
Źródło:: Opuscula Mathematica; 2021, 41, 5; 725-740
1232-9274
2300-6919
Pojawia się w:: Opuscula Mathematica
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Large and moderate deviation principles for nonparametric recursive kernel distribution estimators defined by stochastic approximation method
Autorzy:: Slaoui, Yousri
Powiązania:: https://bibliotekanauki.pl/articles/254712.pdf
Data publikacji:: 2019
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: distribution estimation
stochastic approximation algorithm large and moderate deviations principles
Opis:: In this paper we prove large and moderate deviations principles for the recursive kernel estimators of a distribution function defined by the stochastic approximation algorithm. We show that the estimator constructed using the stepsize which minimize the Mean Integrated Squared Error (MISE) of the class of the recursive estimators defined by Mokkadem et al. gives the same pointwise large deviations principle (LDP) and moderate deviations principle (MDP) as the Nadaraya kernel distribution estimator.
Źródło:: Opuscula Mathematica; 2019, 39, 5; 733-746
1232-9274
2300-6919
Pojawia się w:: Opuscula Mathematica
Dostawca treści:: Biblioteka Nauki

Artykuł

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