WELLMANN, R., Stanislav KATINA and Ch.H. MULLER. Calculation of simplicial depth estimators for polynomial regression with applications. Computational Statistics & Data Analysis. Amsterdam: Elsevier, 2007, vol. 51, No 10, p. 5025-5040. ISSN 0167-9473. Available from: https://dx.doi.org/10.1016/j.csda.2006.10.015.
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Basic information
Original name Calculation of simplicial depth estimators for polynomial regression with applications
Authors WELLMANN, R. (276 Germany), Stanislav KATINA (703 Slovakia, guarantor, belonging to the institution) and Ch.H. MULLER (276 Germany).
Edition Computational Statistics & Data Analysis, Amsterdam, Elsevier, 2007, 0167-9473.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10101 Pure mathematics
Country of publisher Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 1.029
RIV identification code RIV/00216224:14310/07:00061104
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1016/j.csda.2006.10.015
UT WoS 000246681500019
Keywords in English Polynomial regression; Simplicial depth; Maximum depth estimator; Distribution free tests; One-sample tests; Two-sample tests; Shape analysis
Tags International impact, Reviewed
Changed by Changed by: doc. PaedDr. RNDr. Stanislav Katina, Ph.D., učo 111465. Changed: 21/2/2013 13:49.
Abstract
A fast algorithm for calculating the simplicial depth of a single parameter vector of a polynomial regression model is derived. Additionally, an algorithm for calculating the parameter vectors with maximum simplicial depth within an affine subspace of the parameter space or a polyhedron is presented. Since the maximum simplicial depth estimator is not unique, l1 and l2 methods are used to make the estimator unique. This estimator is compared with other estimators in examples of linear and quadratic regression. Furthermore, it is shown how the maximum simplicial depth can be used to derive distribution-free asymptotic alpha-level tests for testing hypotheses in polynomial regression models. The tests are applied on a problem of shape analysis where it is tested how the relative head length of the fish species Lepomis gibbosus depends on the size of these fishes. It is also tested whether the dependency can be described by the same polynomial regression function within different populations.
Links
CZ.1.07/2.2.00/15.0203, interní kód MUName: Univerzitní výuka matematiky v měnícím se světě (Acronym: Univerzitní výuka matematiky)
Investor: Ministry of Education, Youth and Sports of the CR, 2.2 Higher education
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