1,720,991 research outputs found
Local scoring rules: A versatile tool for inference
No full textIn many applications of highly structured statistical models the likelihood function is intractable; in particular, finding the normalisation constant of the distribution can be demanding. One way to sidestep this problem is to to adopt composite likelihood methods, such as the pseudo-likelihood approach. In this paper we display composite likelihood as a special case of a general estimation technique based on proper scoring rules, which supply an unbiased estimating equation for any statistical model. The important class of key local scoring rules avoids the need to compute normalising constants.
Another application arises in Bayesian model selection. The log Bayes factor measures by how much the predictive log score for one model improves on that for another. However, Bayes factors are not
well-defined when improper prior distributions are used. If we replace the log score by a suitable local proper scoring rule, these problems are avoided
A Measure of Local Sensitivity for Proper Scoring Rules in a Bayesian Setting
No full textSuppose to express the uncertainty about an unobserved quantity by quoting a distribution over , after which Nature reveals the value of . A {\em Scoring Rule} e provides a way of judging the quality of a quoted probability distribution for in the light of its outcome . It is called proper if honesty is your best policy, i.e. when you believe X has distribution P in M, your expected score is optimized by the choice Q=P. Every statistical decision problem induces a proper scoring rule.
In this work we propose a general definition of local sensitivity index for Proper Scoring Rules from a Bayesian decision point of view. We show as this new index is an intrinsic characteristic of the class M
Estimation of Spatial Processes Using Local Scoring Rules
No full textWe display pseudo-likelihood as a special case of a general estimation technique based on proper scoring rules. Such a rule supplies an unbiased estimating equation for any statistical model, and this can be extended to allow for missing data. When the scoring rule has a simple local structure, as in many spatial models, the need to compute problematic normalising constants is avoided. We illustrate the approach through an analysis of data on disease in bell pepper plants
Local scoring rules for spatial processes
Full text linkWe display pseudo-likelihood as a special case of a general estimation technique based on proper scoring rules. Such a rule supplies an unbiased estimating equation for any statistical model, and this can be extended to allow for missing data. When the scoring rule has a simple local structure, as in many spatial models, the need to compute problematic normalising constants is avoided. We
illustrate the approach through an analysis of data on disease in bell pepper plants
On the different structures of posterior distributions with respect to the prior distribution
No full text
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
- …
