Statistical matching consists in estimating the joint characteristics of two or more variables observed in two distinct sample surveys. The absence of joint information on the pair of variables of interest leads to uncertainty on the data generating model. The aim of this paper is to analyze the uncertainty in statistical matching in a nonparametric setting. More specifically, an overall measure of uncertainty for non identifiable models is introduced and the effect on model uncertainty due to the introduction of logical constraints is evaluated.
CONTI P., L., Marella, D., Scanu, M. (2010). Uncertainty in statistical matching under logical constraints: a nonparametric approach. In XLV Riunione Scientifica della Società Italiana di Statistica. http://tinyurl.com/38tfw55. CLEUP – Padova.
Uncertainty in statistical matching under logical constraints: a nonparametric approach
MARELLA, Daniela;
2010-01-01
Abstract
Statistical matching consists in estimating the joint characteristics of two or more variables observed in two distinct sample surveys. The absence of joint information on the pair of variables of interest leads to uncertainty on the data generating model. The aim of this paper is to analyze the uncertainty in statistical matching in a nonparametric setting. More specifically, an overall measure of uncertainty for non identifiable models is introduced and the effect on model uncertainty due to the introduction of logical constraints is evaluated.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
