1,720,964 research outputs found
Population distribution over time: modelling local spatial dependence with a CAR process
Full text linkThe effectiveness of local spatial dependence in shaping the population density distribution is investigated. Individual location preferences are modelled by considering the status-related features of a given spatial unit and its neighbours as well as local random spatial dependence. The novelty is framing such a dependence through conditionally autoregressive (CAR) census random effects that are added to a spatially lagged explanatory variable X (SLX) setting. The results not only confirm that controlling for the spatial dimension is relevant but also indicate that local spatial dependence warrants consideration when determining the population distribution of recent decades. In this respect, the framework turns out to be useful for the analysis of microdata in which individual relationships (in a same spatial unit) enforce local spatial dependence
Estimation of spatial econometric linear models with large datasets: How big can spatial Big Data be?
Full text linkSpatial econometrics is currently experiencing the Big Data revolution both in terms of the volume
of data and the velocity with which they are accumulated. Regional data, employed traditionally in
spatial econometric modeling, can be very large, with information that are increasingly available at
a very fine resolution level such as census tracts, local markets, town blocks, regular grids or other
small partitions of the territory. When dealing with spatial microeconometric models referred to the
granular observations of the single economic agent, the number of observations available can be a lot
higher. This paper reports the results of a systematic simulation study on the limits of the current
methodologies when estimating spatial models with large datasets. In our study we simulate a Spatial
Lag Model (SLM), we estimate it using Maximum Likelihood (ML), Two Stages Least Squares (2SLS)
andBayesianestimator(B),andwetesttheirperformancesfordifferentsamplesizesanddifferentlevels
of sparsity of the weight matrices. We considered three performance indicators, namely: computing
time, storage required and accuracy of the estimators. The results show that using standard computer
capabilities the analysis becomes prohibitive and unreliable when the sample size is greater than 70,000
evenforlowlevelsofsparsity. Thisresultsuggeststhatnewapproachesshouldbeintroducedtoanalyze
the big datasets that are quickly becoming the new standard in spatial econometrics
Estimating Uncertainty in Epidemic Models: An Application to COVID-19 Pandemic in Italy
No full textTraditional epidemic models, like the classical SIR, are fitted to real data using deterministic optimization techniques. As a consequence, their performances cannot be properly assessed and, more importantly, the estimates of the critical epidemic parameters (which are of dramatic importance in monitoring the epidemic evolution) cannot be complemented with the calculation of confidence intervals. The aim of the present work is to remove such limitations and to compare the results obtained using two stochastic versions of deterministic SIR models. We describe the two alternatives and the associated estimation procedures, and we apply the two methodologies to a set of COVID-19 data observed in Italy in the 2020 pandemic wave. Our estimates of the basic reproduction number are comparable with the official sources, but using our methods uncertainty can also be properly assessed
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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