1,720,979 research outputs found
Evaluation of matching noise for imputation techniques based on nonparametric local linear regression estimators
No full textA new matching procedure based on imputing missing data by means of a local linear estimator of the underlying population regression function (that is assumed not 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 the variables of interest is assumed not necessarily linear. Performance is measured by the matching noise given by the discrepancy between the distribution generating genuine data and the distribution generating imputed values. (C) 2008 Elsevier B.V. All rights reserved
Uncertainty analysis for statistical matching of ordered categorical variables
No full textThe aim is to analyze the uncertainty in statistical matching for ordered categorical variables. Uncertainty in statistical matching consists in estimating a joint distribution by observing only samples from its marginals. Unless very restrictive conditions are met, observed data do not identify the joint distribution to be estimated, and this is the reason of uncertainty. The notion of uncertainty is first formally introduced, and a measure of uncertainty is then proposed. Moreover, the reduction of uncertainty in the statistical model due to the introduction of logical constraints is investigated and evaluated via simulation. © 2013 Elsevier B.V. All rights reserved
On the Matching Noise of some Nonparametric Imputation Procedures
No full textThe aim of the paper is to evaluate the matching noise produced by nonparametric imputation techniques referring to the kNN method, both with fixed and variable number of donors k. The matching noise is evaluated formally and via a simulation
Publishing Official Classifications in Linked Open Data
No full textData 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 official and wide-recognized classifications (i.e., taxonomies, schemes, code-lists) to be used in the jurisdiction of reference. On a different perspective, there has been much work from the Web data management community to publish data on the Web in an interoperable way. The efforts have converged on a series of standards and practices gathered under the Semantic Web stack. Clearly, the two mentioned scenarios are complementary as they can benefit one to another. To this concern, the Italian Institute of Statistics (Istat) and the Agency for Digital Italy (AgID) have launched an initiative aiming at producing official classifications under the form of Linked Open Data to be published in the Web of data using standard ontologies. The paper describes and motivates this initiative
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
