1,721,043 research outputs found
Analysis of Italian Rainfall Data with a Hierarchical Bayesian Space-Time Model
No full textClimate and meteorological data are characterised by many different scales of spatial and temporal variability often in conjunction with non stationarity, anisotropy and quite complicated space-time interactions. Furthermore climate and meteorological studies must be carried out on large amount of data, often coming from different sources, in order to capture long and short term dependencies, large and small scale spatial effects. All this leads to severe computational problems and the need for the development of complex ad hoc models. Furthermore, for this reason, meteorologists are often constrained to apply potentially unrealistic simplifying assumptions in order to adopt standard statistical models. This kind of models, generally, assume spatial data to be temporally independent and spatial structure not varying over time (separable covariance structure) to estimate the spatial correlation structure and it do not consider the temporal dynamic of the process and the temporal correlation as a function of the spatial domain (Royle, 2000). These limitations can severely affect the estimates quality and the efficiency of traditional space-time statistical models and methods. Alternative models are relatively easy to formulate in the traditional LMM or GLMM frameworks, but a lack of understanding of the underlying processes and the “curse of dimensionality” make the implementation of these models challenging (Wikle et al., 2002). The Bayesian framework represents a natural way to analyse spatio-temporal data and it gives the concrete possibility to overcome the afore mentioned limits (Berliner, Levine and Shea, 2000). In particular, the hierarchical Bayesian space-time modelling approach allows to deal with space-time dependence and interactions by modelling all the relevant process component in several stages. Such models become feasible to implement in high dimensions. Several recent example of Bayesian hierarchical models are present in the literature: for an extensive review see Huang et al., 2007, Benerjee, Carlin and Gelfand, 2004, Wikle et al. 2003 and Wikle, 2000. In this paper we consider a hierarchical Bayesian space-time model, proposed in Wikle, Berliner and Cressie, 1998, to treat monthly rainfall data related to the Italian area and collected between January 2003 and December 2006. The choice of such model is strictly related to the own features of the precipitation process. It’s fairly well known that precipitation process involves complicated spatial structure, temporal structure and spatio-temporal interactions and that the interest of meteorologist are properly in the understanding the behaviour of this process features in order to build prediction maps or hydrological balance equations and so on. These considerations combined with the further necessity of working with a large dataset don’t allow the use of standard statistical approaches and can be more effectively treated in the hierarchical Bayesian space-time modelling approach. Indeed the chosen model allows us to provide a mechanism for combining data from very different sources; to incorporate physical knowledge and background science in the model development and in the specifications of priors on model parameters; to provide posterior distributions of quantities of interest which can be used for scientific inference strategy and to work with very large datasets. These advantages are reached by the model specification through the following five hierarchical levels: 1) the measurement process, as the precipitation process plus an error term; 2) the large and small scales features, incorporated as a linear combination of three sources of variation: time, space and space-time interaction; 3) model parameters: each of these sources are then represented according to physical knowledge; 4 and 5) priors on parameters and hyperpriors are specified respectively in the fourth and fifth stage to complete the model specification. In Particular in the second stage one can decompose the precipitation process into three meaningful components letting the meteorologist to be able to understand and measure how the rainfall is determined by the spatial effect, by the temporal seasonality and by the space-time interactions too. In this stage, the pure spatial and temporal effect describe the well known climate effect whereas the dynamical short time and small spatial scale effect can be easily interpreted as the weather contribution. In this way the rainfall amount in a given site depends on its spatial location and on which period it has been observed as a consequence of the climate effect but it surely depends also on what had happened in the neighbouring sites and previously in time, in other words on the weather contribution. The estimation of such flexible model is obtain through a complex and computer intensive MCMC procedure. Moreover many of the advances in hierarchical Bayesian spatio-temporal modelling have been properly due to the application of the recent MCMC techniques to the Bayesian theory (Wikle et al., 2002). The aim of the present work is to estimate and to understand the spatial and the temporal large scale features (climate effect) of the precipitation process and to isolate them from the spatio-temporal ones (weather effect) for the Italian area. The obtained information are, in a further step, used to obtain predictions maps. The computations are developed by the authors using the R software environment (Development Core Team, 2007)
A Hierarchical Bayesian Space-Time Model to Analyse the Spatio-Temporal Distribution of the Precipitation in the Italian Area
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
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
- …
