1,721,168 research outputs found
Mahanaloris P.C., Majumdar D.N. et Rao C.R. — Anthropométric survey of the United provinces, 1941 : a statistical study
No full textB H. Mahanaloris P.C., Majumdar D.N. et Rao C.R. — Anthropométric survey of the United provinces, 1941 : a statistical study. In: Population, 5ᵉ année, n°1, 1950. pp. 186-187
Bayesian modelling and inference on mixtures of distributions
No full textAbstract only:\ud
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Today’s data analysts and modellers are in the luxurious position of being able to more closely describe, estimate, predict and infer about complex systems of interest, thanks to ever more powerful computational methods but also wider ranges of modelling distributions. Mixture models constitute a fascinating illustration of these aspects: while within a parametric family, they offer malleable approximations in non-parametric settings; although based on standard distributions, they pose highly complex computational challenges; and they are both easy to constrain to meet identifiability requirements and fall within the class of ill-posed problems. They also provide an endless benchmark for assessing new techniques, from the EM algorithm to reversible jump methodology. In particular, they exemplify the formidable opportunity provided by new computational technologies like Markov chain Monte Carlo (MCMC) algorithms. It is no coincidence that the Gibbs sampling algorithm for the estimation of mixtures was proposed before (Tanner and Wong 1987) and immediately after (Diebolt and Robert 1990c) the seminal paper of Gelfand and Smith (1990): before MCMC was popularised, there simply was no satisfactory approach to the computation of Bayes estimators for mixtures of distributions, even though older importance sampling algorithms were later discovered to apply to the simulation of posterior distributions of mixture parameters (Casella et al. 2002).\ud
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Bayesian approaches to mixture modelling have attracted great interest among researchers and practitioners alike. The Bayesian paradigm (Berger 1985, Besag et al. 1995, Robert 2001, see, e.g.,) allows for probability statements to be made directly about the unknown parameters, prior or expert opinion to be included in the analysis, and hierarchical descriptions of both local-scale and global features of the model. This framework also allows the complicated structure of a mixture model to be decomposed into a set of simpler structures through the use of hidden or latent variables. When the\ud
number of components is unknown, it can well be argued that the Bayesian paradigm is the only sensible approach to its estimation (Richardson and Green 1997).\ud
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This chapter aims to introduce the reader to the construction, prior modelling, estimation and evaluation of mixture distributions in a Bayesian paradigm. We will show that mixture distributions provide a flexible, parametricframework for statistical modelling and analysis. Focus is on methods rather than advanced examples, in the hope that an understanding of the practical aspects of such modelling can be carried into many disciplines. It also stresses implementation via specific MCMC algorithms that\ud
can be easily reproduced by the reader. In Section 1.2, we detail some basic properties of mixtures, along with two different motivations. Section 1.3 points out the fundamental difficulty in doing inference with such objects, along with a discussion about prior modelling, which is more restrictive than usual, and the constructions of estimators, which also is more involved than the standard posterior mean solution. Section 1.4 describes the completion and non-completion MCMC algorithms that can be used\ud
for the approximation to the posterior distribution on mixture parameters, followed by an extension of this analysis in Section 1.5 to the case in which the number of components is unknown and may be estimated by Green's (1995) reversible jump algorithm and Stephens' 2000 birth-and-death procedure.\ud
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Section 1.6 gives some pointers to related models and problems like mixtures of regressions (or conditional mixtures) and hidden Markov models (or dependent mixtures), as well as Dirichlet priors
The quest for nonlinearity in time series
No full textIn this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss the definition and the properties of linear processes and the implications that such properties have on the operational strand. Then, we present and review a tentative classification of the various tests that can be found both in the
time series and in the nonlinear dynamics literature. Two main factors contributed to the production of a plethora of alternatives for assessing nonlinearity in time series: the first factor is the intrinsic asymmetry between the linear and the nonlinear
realm. In fact, there can be departures from linearity in various directions as nonlinear phenomena possess a virtually infinite richness of features. Among such features we can mention irreversibility, nonuniform predictability, noise amplification/
suppression, phase synchronization, noise-induced phenomena, sensitivity to initial conditions, and so on. The second factor is the multidisciplinary nature of the problem. Indeed, the problem of characterizing the various aspects of nonlinear processes is shared among different disciplines, such as Statistics, Econometrics,
Nonlinear Dynamics, Biology, and Engineering. The review is by no means exhaustive and reflects the personal inclinations of the autho
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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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