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21 November 2019
Doctoral thesis (Dissertations and theses)
Contributions to spatial data analysis and Stein's method
Ernst, Marie 
2019
 

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MErnst_thesis.pdf
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PhDDefense_MErnst-17dec.pdf
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Keywords :
Spatial data analysis; Robust statistics; Local outliers; Spatial autocorrelation; Stein's method; Covariance expansion; Stein equations; Stein factors; Total variation distance; Wasserstein distance; Kolmogorov distance; Integral probability metrics
Abstract :
[en] The thesis consists of two parts. The first part is rooted in robust statistics, and more precisely in local outlier detection in spatial multivariate data, and the robustness of tests concerning autocorrelation. The second part deals with the probabilistic method developed by Charles Stein. In the thesis, Stein's method was linked to first order covariance relations, infinite covariance expansions, and distances between probability distributions.
Disciplines :
Mathematics
Author, co-author :
Ernst, Marie  ;  Université de Liège - ULiège > Département de mathématique > Département de mathématique
Language :
English
Title :
Contributions to spatial data analysis and Stein's method
Defense date :
17 December 2019
Institution :
ULiège - Université de Liège
Degree :
Docteur en Sciences
Promotor :
Haesbroeck, Gentiane ;  Université de Liège - ULiège > Mathematics
Swan, Yvik ;  Université de Liège - ULiège > Département de mathématique
President :
Lambert, Philippe ;  Université de Liège - ULiège > Mathematics
Jury member :
Berckmoes, Ben
Ley, Christophe
Reinert, Gesine

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