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Statistical matching is a technique for combining information from different sources. It can be used in situations when variables of interest are not jointly observed and conclusions must be drawn on the basis of partial knowledge of the phenomenon. Uncertainty regarding conclusions arises naturally unless strong and nontestable hypotheses are assumed.(More)
A new matching procedure based on imputing missing data by means of a local linear estimator of the underlying population regression function (that is assumednot necessarily linear) is introduced. Such a procedure is compared to other traditional approaches, more precisely hot deck methods as well as methods based on kNN estimators. The relationship between(More)
Data interoperability is well recognized as a basic step for developing integrated services supporting inter-organizations communication. The issue of ensuring data interoperability has been tackled by many different communities in order to address various problems. In particular, the (over-)national institutes of statistics deeply concern the issuing of(More)
Record Linkage (RL) refers to the use of an algorithmic technique to match records from different data sets that correspond to the same statistical unit. RL is ubiquitous in official statistics: estimation of population size via capture-recapture methods, testing of disclosure strategies and coverage measurement surveys are only few examples. A key(More)
We propose a novel methodology based on the concept of Bayesian network (BN, see Cowell et al., 1999) for the estimation of a joint probability distribution of a set of categorical variables when samples are drawn according to complex survey designs. Note that, restricting ourselves to categorical variables, the previous aim corresponds to estimation of a(More)
A class of estimators based on the dependency structure of a multivariate variable of interest and the survey design is defined. The dependency structure is the one described by the Bayesian networks. This class allows ratio type estimators as a subclass identified by a particular dependency structure. It will be shown by a MonteCarlo simulation how the(More)
2 The purpose of this paper is to evaluate the possibility of applying statistical matching on two different data sources to create an integrated database with detailed information on households income and consumption expenditures in Italy. The data to integrate are those of EU-SILC (EU Statistics on Income and Living Condition) 2012, with income reference(More)
The problem of monitoring and managing the data production process by means of process flow indicators is presented in a decision theory framework. Here it is shown how to represent and solve the decision problem via influence diagrams, i.e. Bayesian network supporting decisions. An illustrative example is provided.
In the last years, interest on Statistical Matching problems has increased (Rässler, 2002, D’Orazio et al. 2006). This is due to the large amount of data-sets available and, at the same time, to the need of timely and not costly information. Statistical Matching techniques aim at combining information from different sources. In particular, it is assumed(More)