RT Journal Article
T1 Bayesian influence diagnostics in radiocarbon dating
A1 Fernández-Ponce, J.M.
A1 Palacios-Rodríguez, F.
A1 Rodríguez-Griñolo, Rosario
K1 Conditional bias
K1 Influence analysis
K1 Outliers
K1 Predictive approach
K1 Radiocarbon dating
AB Linear 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.
PB Taylor & Francis
YR 2013
FD 2013-01
LK https://hdl.handle.net/10433/21511
UL https://hdl.handle.net/10433/21511
LA en
NO Journal of Applied Statistics, vol 40,nº 1,p. 28-39
NO Departamento de Economía, Métodos Cuantitativos e Hª Económica, Área de Estadísitca e I.O. Universidad Pablo de Olavide
NO Deoartamento de Estadísitca e I.O. Universidad de Sevilla
DS RIO
RD Apr 23, 2026