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191.
Pierre Bauduin 《Early Medieval Europe》2021,29(3):394-416
In his Gesta Normannorum Ducum, William of Jumièges related that the Danish king Swein Forkbeard, at the outset of his conquest of England, came to Rouen and met Richard II. Both leaders negotiated a peace agreement that authorized the Danes to sell their booty in Normandy and provided them with assistance and security. This article examines the circumstances and the clauses of the agreement and its place in the narrative of the Gesta. The author linked the circumstances of the agreement to the St Brice’s Day massacre, which provided him with the opportunity to present a very negative portrait of King Æthelred II. While one should be very careful about the author's claims and chronology, a comparison with other similar agreements renders the terms of the treaty, as related by William, plausible. 相似文献
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Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms 总被引:1,自引:0,他引:1
This article presents a geostatistical methodology that accounts for spatially varying population size in the processing of cancer mortality data. The approach proceeds in two steps: (1) spatial patterns are first described and modeled using population-weighted semivariogram estimators, (2) spatial components corresponding to nested structures identified on semivariograms are then estimated and mapped using a variant of factorial kriging. The main benefit over traditional spatial smoothers is that the pattern of spatial variability (i.e., direction-dependent variability, range of correlation, presence of nested scales of variability) is directly incorporated into the computation of weights assigned to surrounding observations. Moreover, besides filtering the noise in the data, the procedure allows the decomposition of the structured component into several spatial components (i.e., local versus regional variability) on the basis of semivariogram models. A simulation study demonstrates that maps of spatial components are closer to the underlying risk maps in terms of prediction errors and provide a better visualization of regional patterns than the original maps of mortality rates or the maps smoothed using weighted linear averages. The proposed approach also attenuates the underestimation of the magnitude of the correlation between various cancer rates resulting from noise attached to the data. This methodology has great potential to explore scale-dependent correlation between risks of developing cancers and to detect clusters at various spatial scales, which should lead to a more accurate representation of geographic variation in cancer risk, and ultimately to a better understanding of causative relationships. 相似文献
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