1,720,959 research outputs found
Modeling dependence across stock markets using copulas.
No full textAn important issue in multivariate statistical modeling is the choice of the appropriate dependence measure. Correlation has many pitfalls as it is associated with the elliptical distributions assumption of normality which fails in the presence of extreme endpoints either in marginals or in higher dimensions. Copulas offer an alternative measure of dependence which overcomes the limitations of correlation, and they also determine the type of dependence whether it is linear, upper tail or lower tail. This research serves to explore the appropriateness of copulas in modeling bivariate dependence amongst five SADC stock markets with an objective of assessing the effectiveness of regional integration. Archimedean copulas, due to their desirable properties, were examined using both parametric and non-parametric techniques.
Non-parametric estimation gave profound results signifying the appropriateness of the Gumbel copula in dependence modeling which indicated that investors had chances of portfolio diversification across the region as the markets were prone to booming together
Handling Complexity Via Statistical Methods
No full textPhenomena investigated from complex systems are characteristically dynamic, multi-dimensional, and nonlinear. Their traits can be captured through data generating mechanisms (DGM) that explain the interactions among the systems’ components. Measurement is fundamental to advance science, and complexity requires deviation from linear thinking to handle it. Simplifying the measurement of complex and heterogeneity of data in statistical methodology can compromise their accuracy. In particular, conventional statistical methods make assumptions on the DGM that are rarely met in real world, which can make inference inaccurate. We posit that causal inference for complex systems phenomena requires at least the incorporation of subject-matter knowledge and use of dynamic metrics in statistical methods to improve on its accuracy.This thesis consists of two separate topics on handling data and data generating mechanisms complexities: the evaluation of bundled nutrition interventions and modeling atmospheric data.Firstly, when a public health problem requires multiple ways to address its contributing factors, bundling of the approaches can be cost-effective. Scaling up bundled interventions geographically requires a hierarchical structure in implementation, with central coordination and supervision of multiple sites and staff delivering a bundled intervention. The experimental design to evaluate such an intervention becomes complex to accommodate the multiple intervention components and hierarchical implementation structure. The components of a bundled intervention may impact targeted outcomes additively or synergistically. However, noncompliance and protocol deviation can impede this potential impact, and introduce data complexities. We identify several statistical considerations and recommendations for the implementation and evaluation of bundled interventions.The simple aggregate metrics used in clustering randomized controlled trials do not utilize all available information, and findings are prone to the ecological fallacy problem, in which inference at the aggregate level may not hold at the disaggregate level. Further, implementation heterogeneity impedes statistical power and consequently the accuracy of the inference from conventional comparison with a control arm. The intention-to-treat analysis can be inadequate for bundled interventions. We developed novel process-driven, disaggregated participation metrics to examine the mechanisms of impact of the Agriculture to Nutrition (ATONU) bundled intervention (ClinicalTrials.gov Identifier: NCT03152227). Logistic and beta-logistic hierarchical models were used to characterize these metrics, and generalized mixed models were employed to identify determinants of the study outcome, dietary diversity for women of reproductive age. Mediation analysis was applied to explore the underlying determinants by which the intervention affects the outcome through the process metrics. The determinants of greater participation should be the targets to improve implementation of future bundled interventions.Secondly, observed atmospheric records are often prohibitively short with only one record typically available for study. Classical nonlinear time series models applied to explain the nonlinear DGM exhibit some statistical properties of the phenomena being investigated, but have nothing to do with their physical properties. The data’s complex dependent structure invalidates inference from classical time series models involving strong statistical assumptions rarely met in real atmospheric and climate data. The subsampling method may yield valid statistical inference. Atmospheric records, however, are typically too short to satisfy asymptotic conditions for the method’s validity, which necessitates enhancements of subsampling with the use of approximating models (those sharing statistical properties with the series under study)
Modeling Dependence across Stock Markets using Copulas
No full textAn important issue in multivariate statistical modeling is the choice of the appropriate
dependence measure. Correlation has many pitfalls as it is associated with
the elliptical distributions assumption of normality which fails in the presence of
extreme endpoints either in marginals or in higher dimensions. Copulas offer an alternative
measure of dependence which overcomes the limitations of correlation, and
they also determine the type of dependence whether it is linear, upper tail or lower
tail. This research serves to explore the appropriateness of copulas in modeling bivariate
dependence amongst five SADC stock markets with an objective of assessing
the effectiveness of regional integration. Archimedean copulas, due to their desirable
properties, were examined using both parametric and non-parametric techniques.
Non-parametric estimation gave profound results signifying the appropriateness of the
Gumbel copula in dependence modeling which indicated that investors had chances
of portfolio diversification across the region as the markets were prone to booming
together
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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