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of 425
pro vyhledávání: '"Spencer, Neil A."'
Autor:
Spencer, Neil A., Miller, Jeffrey W.
This article establishes novel strong uniform laws of large numbers for randomly weighted sums such as bootstrap means. By leveraging recent advances, these results extend previous work in their general applicability to a wide range of weighting proc
Externí odkaz:
http://arxiv.org/abs/2209.04083
Publikováno v:
Work Organisation, Labour & Globalisation, 2023 Jan 01. 17(2), 47-70.
Externí odkaz:
https://www.jstor.org/stable/48755813
Factorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process response. In the statistics literature, several studies have investigated the anal
Externí odkaz:
http://arxiv.org/abs/2012.08089
Latent position network models are a versatile tool in network science; applications include clustering entities, controlling for causal confounders, and defining priors over unobserved graphs. Estimating each node's latent position is typically fram
Externí odkaz:
http://arxiv.org/abs/2006.07687
Autor:
Spencer, Neil A., Murray, Jared S.
When a latent shoeprint is discovered at a crime scene, forensic analysts inspect it for distinctive patterns of wear such as scratches and holes (known as accidentals) on the source shoe's sole. If its accidentals correspond to those of a suspect's
Externí odkaz:
http://arxiv.org/abs/1906.05244
Publikováno v:
Work Organisation, Labour & Globalisation, 2022 Jan 01. 16(1), 7-13.
Externí odkaz:
https://www.jstor.org/stable/48675866
Publikováno v:
Work Organisation, Labour & Globalisation, 2022 Jan 01. 16(1), 34-51.
Externí odkaz:
https://www.jstor.org/stable/48675868
Akademický článek
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Autor:
Kanji, Rahim, Gue, Ying X., Farag, Mohamed F., Spencer, Neil H., Mutch, Nicola J., Gorog, Diana A.
Publikováno v:
In JACC: Basic to Translational Science November 2022 7(11):1069-1082
When modeling network data using a latent position model, it is typical to assume that the nodes' positions are independently and identically distributed. However, this assumption implies the average node degree grows linearly with the number of node
Externí odkaz:
http://arxiv.org/abs/1709.09702