941 resultados para Multivariate Statistics


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Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations nor do they deal with dependency. This paper describes a mathematical procedure for analyzing dyadic interactions in a social system. The proposed method mainly consists of decomposing asymmetric data into their symmetrical and skew-symmetrical parts. A quantification of skew-symmetry for a social system can be obtained by dividing the norm of the skew-symmetrical matrix by the norm of the asymmetric matrix. This calculation makes available to researchers a quantity related to the amount of dyadic reciprocity. Regarding agents, the procedure enables researchers to identify those whose behavior is asymmetric with respect to all agents. It is also possible to derive symmetric measurements among agents and to use multivariate statistical techniques.

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BACKGROUND AND PURPOSE: There are few data on long-term clinical results and tolerance of brachytherapy in anal canal cancer. We present one of the largest retrospective analyses of anal canal cancers treated with external beam radiotherapy with/without (±) chemotherapy followed by a brachytherapy boost. MATERIALS AND METHODS: We performed a retrospective analysis of clinical results in terms of efficacy and toxicity. The impact of different clinical and therapeutic variables on these outcomes was studied. RESULTS: From May 1992 to December 2009, 209 patients received brachytherapy after external beam radiotherapy ± chemotherapy. Of these patients, 163 were stage II or stage IIIA (UICC 2002) and 58 were N1-3. According to age, ECOG performance status (PS), and comorbidities, patients received either radiotherapy alone (58/209) or radiochemotherapy (151/209). The median follow-up was 72.8 months. The 5- and 10-year local control rates were 78.6 and 73.9 %, respectively. Globally, severe acute and late G3-4 reactions (NCI-CTC scale v. 4.0) occurred in 11.2 and 6.3 % of patients, respectively. Univariate analysis showed the statistical impact of the pelvic treatment volume (p = 0.046) and of the total dose (p = 0.02) on the risk of severe acute and late toxicities, respectively. Only six patients required permanent colostomy because of severe late anorectal toxicities. CONCLUSION: After a long follow-up time, brachytherapy showed an acceptable toxicity profile and high local control rates in patients with anal canal cancer.

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Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment.

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Social reciprocity may explain certain emerging psychological processes, which are likely to be founded on dyadic relations. Although some indices and statistics have been proposed to measure and make statistical decisions regarding social reciprocity in groups, these were generally developed to identify association patterns rather than to quantify the discrepancies between what each individual addresses to his/her partners and what is received from them in return. Additionally, social researchers are not only interested in measuring groups at the global level, since dyadic and individual measurements are also necessary for a proper description of social interactions. This study is concerned with a new statistic for measuring social reciprocity at the global level and with decomposing it in order to identify those dyads and individuals which account for a significant part of asymmetry in social interactions. In addition to a set of indices some exact analytical results are derived and a way of making statistical decisions is proposed.

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In this article, the fusion of a stochastic metaheuristic as Simulated Annealing (SA) with classical criteria for convergence of Blind Separation of Sources (BSS), is shown. Although the topic of BSS, by means of various techniques, including ICA, PCA, and neural networks, has been amply discussed in the literature, to date the possibility of using simulated annealing algorithms has not been seriously explored. From experimental results, this paper demonstrates the possible benefits offered by SA in combination with high order statistical and mutual information criteria for BSS, such as robustness against local minima and a high degree of flexibility in the energy function.

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Conferència Organitzada per l'Escola Politècnica Superior, Universitat de Vic en col·laboració amb Servei d'Estadística de la Universitat Autònoma de Barcelona i CosmoCaixa Barcelona. Celebrada del 18 al 22 de juny de 2012 a Barcelona

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