1,721,239 research outputs found
Ultrametric models for hierarchical dimensionality reduction
Full text linkMany relevant multidimensional phenomena, such as well-being, climate change, sustainable development, poverty and so on, are defined by nested latent concepts, which can be represented by a tree-shape structure supposing hierarchical relationships among observed variables. In literature, several methodologies have been proposed to both model the relationships among observed variables that reflect unobserved ones, and assess the existence of unobserved variables of "higher-order''. Nonetheless, these methodologies are usually developed with sequential procedures that do not optimize a unique objective function, and/or a confirmatory approach, i.e., by setting the relationships between observed and unobserved variables a priori.
This dissertation discusses some new simultaneous, exploratory and parsimonious models for hierarchical dimensionality reduction, which overcome the limitations of the existing methodologies. The proposals introduced herein are based, "directly'' or "indirectly'', upon the definition of an ultrametric matrix, that differs from the well-known definition of an ultrametric distance matrix and is one-to-one associated with a hierarchy of latent concepts. The first proposal allows to model a nonnegative correlation matrix via an ultrametric correlation one by detecting reliable concepts, associated with disjoint groups of variables, and hierarchical relationships among them. The second work compares the first proposal with the traditional agglomerative hierarchical clustering algorithms applied on variables, after a transformation of correlations into distances, by highlighting the need for specific models to inspect the hierarchical relationships among variables. The third proposal extends the definition of an ultrametric matrix to a generic one by relaxing the non-negativity assumption and applying it to a covariance matrix. The extended ultrametric covariance matrix is then used to model the covariance structures of a Gaussian mixture model by both defining a new parsimonious parameterization of a covariance matrix and inspecting the hierarchical structure underlying multidimensional phenomena in heterogeneous populations. The fourth proposal introduces a quantification of latent concepts via a hierarchical extension of the Disjoint Principal Component Analysis. Even if not directly based on the definition of an ultrametric matrix, this proposal aims in turn at pinpointing nested partitions of variables into groups, each one associated with a component.
The proposed models are illustrated both via simulation studies and real data applications in order to study their performances and abilities
Absence of sign problem in the (saddle point approximation of the) nilpotency expansion of QCD at finite chemical potential
No full textWe have developed a method to derive the (approximate) quark contribution to the fermion free energy of QCD on a lattice, at finite temperature and chemical potential, with Kogut-Susskind fermions in the flavor basis.
We show here the expression at zero temperature. This result has been obtained at the lowest order of the nilpotency expansion. At this order the well known ``sign problem" does not arise and the quark contribution to the action can be used as a statistical weight in the Monte Carlo simulations
Diquarks in the nilpotency expansion of QCD and their role at finite chemical potential
No full textWe assume that the most important quark correlations are pairwise at all baryon densities. We introduce correlated pairs by means of Bogoliubov transformations which are functions of time and spatial gauge fields, in the formalism of the transfer matrix with lattice regularization. The dependence on time and gauge fields allows us to enforce gauge invariance and other symmetries in the transformed quantities in the same way as in the original ones. We derive the quark contribution to the free energy at finite chemical potential in a certain approximation. Its expression cannot be evaluated analytically, but it has a definite sign
Lauren R. Donaldson, left, and Ralph F. Palumbo standing on the lagoon beach of Eniwetok Island, summer 1964
No full textImages documenting the Radiological Survey of Eniwetok, Bikini and Rongelap Atolls between July and September 1964.
Caption with image: Lauren R. Donaldson, left, laboratory director, and Ralph F. Palumbo, assistant expedition director and botanist, take a walk on the lagoon beach of Eniwetok Island, near the Eniwetok Marine Biological Laboratory. In the background is the rusty wreck of a Navy patrol craft, which went aground during the American invasion of Eniwetok in February 1944. 9238-10A
Radiological Survey of Bikini, Eniwetok and Rongelap Atolls, Vol. 2, p.2
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
Cladag 2013. 9th Meeting of the Classification and Data Analysis Group. Book of Abstracts
No full textThe 9th biennal international meeting of the Classification and Data Analysis Group of the Italian Statistical Society took place at the University of Modena and Reggio Emilia, from September 18th to September 20th, 2013. The present book contains the short papers presented during this meeting
Latent ties identification in inter-firms social networks
No full textSocial networks are usually analyzed through manifest variables. However there are social latent aspects that strongly qualify the networks. This paper aims to propose a statistical methodology to identify latent variable in inter-firm social networks. A multidimensional scaling technique is proposed to measure this latent variable as a combination of an appropriate set of two or more manifest relational aspects. This method, tested on an inter-firm social network in theMarche region, is a new way to grasp social aspect with quantitative tools that could be implemented
under several different conditions, using also other variable
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