Fernández Ponce, José MaríaPalacios Rodríguez, FátimaRodríguez Griñolo, María del Rosario2024-09-202024-09-202012-08-27Fernández Ponce, J.M., Palacios Rodríguez, F. y Rodríguez Griñolo, M.d.R. (2012). Bayesian Influence Diagnostics in Radiocarbon Dating. Journal of Applied Statistics, 40 (1). https://doi.org/10.1080/02664763.2012.725531.0266-47631360-0532https://hdl.handle.net/11441/162690Linear models constitute the primary statistical technique for any experimental science. A major topic in this area is the detection of influential subsets of data, that is, of observations that are influential in terms of their effect on the estimation of parameters in linear regression or of the total population parameters. Numerous studies exist on radiocarbon dating which propose a value consensus and remove possible outliers after the corresponding testing. An influence analysis for the value consensus from a Bayesian perspective is developed in this article.application/pdf22 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Conditional BiasInfluence AnalysisOutliersPredictive ApproachRadiocarbon Datinginfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1080/02664763.2012.725531