1,720,957 research outputs found
Analytic inference in finite population framework via resampling
Full text linkThe aim of this dissertation is to provide nonparametric tools for analytic inference
on superpopulation models. To pursue the goal we approach to the problem in two
different ways. The first one is analytic. Following the classical empirical process
theory, we first derive a functional central limit theorem that fully characterizes
the asymptotic distribution of the Hàjek estimator of the distribution function of
the superpopulation. In addition, assuming some regularity conditions on the (superpopulation)
parameters of interest, we extend this analytic characterization to
a large class of possible paramaters of interest. The second one is more “practical”:
our aim is to construct a computer intensive procedure that allows to infer the
superpopulation, also when the (asymptotic) distribution of an interest parameter
has an unmanageable analytic form. Clearly, such a procedure is resampling. Unfortunately,
the most famous resampling technique, the bootstrap procedure, does
not work in our framework. In fact, in the finite population framework, even if a
superpopulation is assumed, the units cannot be assumed independent in the presence
of a non trivial sampling design. This fact makes the classic bootstrap fail.
Of course, in the survey sampling literature, resampling procedure have been proposed,
but we haven not resort to them because of two reasons: i) a largest part of
these resampling techniques have been developed to infer the finite population and
not the superpopulation; ii) we want to make a parallel between the classical non
parametric theory and survey sampling. Almost all of these procedures are justified
by mimicking the first two moments of the distribution of the considered estimator,
and this is not the argument used to justify Efron’s bootstrap in classical nonparametric
statistics. Thus, we introduce the “ multinomial” scheme as a resampling
procedure for the superpopulation and we provide an asymptotic validation of this
method, that involves the whole distribution of the considered estimators, exactly
as it happens for classic bootstrap. In the last part of this work, the results obtained
are applied to different inferential problems and, for each one of the concerned problem,
a simulation study is performed to test the validity of our proposal. For these
applications, we especially focused on problems where the interest parameter is not
a linear function of the data
On the estimation of the concentration curve under complex sampling designs
No full textThis paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with different inclusion probabilities. The asymptotic law of the finite population version of the concentration process is first studied. Then, a resampling scheme able to approximate such a law is constructed. Finally, an application to the construction of confidence bands is considered
On the estimation of the Lorenz curve under complex sampling designs
No full textThis paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with different inclusion probabilities. A (design-based) Hájek type estimator for the Lorenz curve is
proposed, and its asymptotic properties are studied. Then, a resampling scheme able to approximate the asymptotic law of the Lorenz curve estimator is constructed. Applications are given to the construction of (i) a confidence band for the Lorenz curve, (ii) confidence intervals for the Gini concentration ratio, and (iii) a test for Lorenz dominance. The merits of the proposed resampling procedure are evaluated through a simulation study
On the estimation of the Lorenz curve under complex sampling designs
No full textThis paper focuses on the estimation of the concentration curve of a finite population, when data are collected according to a complex sampling design with different inclusion probabilities. A (design-based) Hájek type estimator for the Lorenz curve is proposed, and its asymptotic properties are studied. Then, a resampling scheme able to approximate the asymptotic law of the Lorenz curve estimator is constructed. Applications are given to the construction of (i) a confidence band for the Lorenz curve, (ii) confidence intervals for the Gini concentration ratio, and (iii) a test for Lorenz dominance. The merits of the proposed resampling procedure are evaluated through
a simulation study
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
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