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Träfflista för sökning "WFRF:(Resnick I) srt2:(2020-2022)"

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1.	Andreakos, E, et al. (author) A global effort to dissect the human genetic basis of resistance to SARS-CoV-2 infection 2022 In: Nature immunology. - : Springer Science and Business Media LLC. - 1529-2916 .- 1529-2908. ; 23:2, s. 159-164 Journal article (peer-reviewed)
2.	Chia, R, et al. (author) Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture 2021 In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 53:3, s. 294- Journal article (peer-reviewed)
3.	Drees, Holger, et al. (author) On a Minimum Distance Procedure for Threshold Selection in Tail Analysis 2020 In: SIAM Journal on Mathematics of Data Science. - : Society for Industrial & Applied Mathematics (SIAM). - 2577-0187. ; 2:1, s. 75-102 Journal article (peer-reviewed)abstract Power-law distributions have been widely observed in different areas of scientific research. Practical estimation issues include selecting a threshold above which observations follow a power-law distribution and then estimating the power-law tail index. A minimum distance selection procedure (MDSP) proposed by Clauset, Shalizi, and Newman [SIAM Rev., 51 (2009), pp. 661-703] has been widely adopted in practice for the analyses of social networks. However, theoretical justifications for this selection procedure remain scant. In this paper, we study the asymptotic behavior of the selected threshold and the corresponding power-law index given by the MDSP. For independent and identically distributed (iid) observations with Pareto-like tails, we derive the limiting distribution of the chosen threshold and the power-law index estimator, where the latter estimator is not asymptotically normal. We deduce that in this iid setting MDSP tends to choose too high a threshold level and show with asymptotic analysis and simulations how the variance increases compared to Hill estimators based on a nonrandom threshold. We also provide simulation results for dependent preferential attachment network data and find that the performance of the MDSP procedure is highly dependent on the chosen model parameters.

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Type of publication: journal article (3)

Type of content: peer-reviewed (3)

Author/Editor: Ferrari, R. (1); Okada, S. (1); Zhang, Q. (1); Aarsland, D (1); Halliday, GM (1); Londos, Elisabet (1); show more...; Marder, K (1); McKeith, IG (1); Galasko, D (1); Casanova, JL (1); Klein, G (1); Bennett, DA (1); Logroscino, G (1); Tanaka, T. (1); Okamoto, K. (1); Calvo, A (1); Novelli, G (1); Pastor, P (1); Ahmed, S. (1); Pan-Hammarstrom, Q (1); Boisson, B (1); Bondarenko, A (1); Sediva, A (1); Shcherbina, A (1); Su, HC (1); Condino-Neto, A (1); Bastard, P (1); Zhang, SY (1); Brodin, P (1); Ferrucci, L (1); Foroud, TM (1); Gibbs, JR (1); Hernandez, DG (1); Nalls, MA (1); Ryten, M (1); Traynor, BJ (1); Moore, A (1); Floris, G (1); Al-Sarraj, S (1); Gentleman, S (1); Duyckaerts, C (1); Parkkinen, L (1); Attems, J. (1); Albani, D (1); Ghetti, B (1); Alcolea, D. (1); Clarimón, J. (1); Fortea, J. (1); Lleó, A. (1); Thomas, AJ (1); show less...

University: Karolinska Institutet (2); Royal Institute of Technology (1); Lund University (1)

Language: English (3)

Research subject (UKÄ/SCB): Natural sciences (1); Medical and Health Sciences (1)

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