Characterization of Glass,Shell, and Fishbone Beads on Ibo Island (Northern Mozambique) in the Context of the Indian Ocean Trade

African Archaeological Review - A set of beads made of glass, gastropod mollusk shell, and fishbone from a Swahili occupation level on Ibo Island (northern Mozambique) is dated to the eleventh and...     

The Santa María pottery of El Bolsón valley (Catamarca,Argentina): Compositional characterization and implications on the elaboration processes,ca. 1000–1600 ce

The results obtained from the multi-analytic compositional characterization of ceramic pastes and paints of the Santa María style, from the El Bolsón valley (Belén Department, Catamarca Province, Argentina), are presented here. This pottery style had a wide regional distribution in Northwestern Argentina between ca. 1000 and1600 ce and is characterized by its complex iconography painted in black, cream and red. The analyses show that the containers correspond to the technical tradition of using grog temper and suggest that its manufacture involved a double firing process. This reveals a new practice for the time.     

Sapwood estimates in the interpretation of tree-ring dates

Many timber finds lack some or all of the outer, sapwood rings formed in the years just before felling. In order to estimate felling date once the outermost remaining ring has been dated, it is necessary to estimate the number of sapwood rings originally present. Methods doing this for oak are reviewed in the light of an intensive study of living trees at one site and an extensive study of 175 samples from living trees in North Wales and northwest England. Some methods reported in the literature are found to be invalid. A method reported by Hollstein (1965) is most reliable, with modifications for known variations in sapwood number with position in the tree. At present the best available estimate is that a value of 30 sapwood rings be used (95% confidence limits: 19–50).     

Bayesian Spatial Filtering for Hedonic Models: An Application for the Real Estate Market

This article presents a Bayesian method based on spatial filtering to estimate hedonic models for dwelling prices with geographically varying coefficients. A Bayesian Adaptive Sampling algorithm for variable selection is used, which makes it possible to select the most appropriate filters for each hedonic coefficient. This approach explores the model space more systematically and takes into account the uncertainty associated with model estimation and selection processes. The methodology is illustrated with an application for the real estate market in the Spanish city of Zaragoza and with simulated data. In addition, an exhaustive comparison study with a set of alternatives strategies used in the literature is carried out. Our results show that the proposed Bayesian procedures are competitive in terms of prediction; more accurate results are obtained in the estimation of the regression coefficients of the model, and the multicollinearity problems associated with the estimation of the regression coefficients are solved.