17 resultados para MEAN VECTOR
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T (2) and the |S| charts. However, these charts have two drawbacks: (1) the T (2) and the |S| statistics are not easy to compute, and (2) after a signal, they do not distinguish the variable affected by the assignable cause. As an alternative to (1), we propose the MVMAX chart, which only requires the computation of sample means and sample variances. As an alternative to (2), we propose the joint use of two charts based on the non-central chi-square statistic (NCS statistic), named as the NCS charts. Once the NCS charts signal, the user can immediately identify the out-of-control variable. In general, the synthetic MVMAX chart is faster than the NCS charts and the joint T (2) and |S| charts in signaling processes disturbances.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The MRMAX chart is a single chart based on the standardized sample means and sample ranges for monitoring the mean vector and the covariance matrix of multivariate processes. User's familiarity with the computation of these statistics is a point in favor of the MRMAX chart. As a single chart, the recently proposed MRMAX chart is very appropriate for supplementary runs rules. In this article, we compare the supplemented MRMAX chart and the synthetic MRMAX chart with the standard MRMAX chart. The supplementary and the synthetic runs rules enhance the performance of the MRMAX chart. © 2013 Elsevier Ltd.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this article, we consider the T(2) chart with double sampling to control bivariate processes (BDS chart). During the first stage of the sampling, n(1) items of the sample are inspected and two quality characteristics (x; y) are measured. If the Hotelling statistic T(1)(2) for the mean vector of (x; y) is less than w, the sampling is interrupted. If the Hotelling statistic T(1)(2) is greater than CL(1), where CL(1) > w, the control chart signals an out-of-control condition. If w < T(1)(2) <= CL(1), the sampling goes on to the second stage, where the remaining n(2) items of the sample are inspected and T(2)(2) for the mean vector of the whole sample is computed. During the second stage of the sampling, the control chart signals an out-of-control condition when the statistic T(2)(2) is larger than CL(2). A comparative study shows that the BDS chart detects process disturbances faster than the standard bivariate T(2) chart and the adaptive bivariate T(2) charts with variable sample size and/or variable sampling interval.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The T-2 and the generalized variance vertical bar S vertical bar charts are used for monitoring the mean vector and the covariance matrix of multivariate processes. In this article, we propose for bivariate processes the use of the T-2 and the VMAX charts. The points plotted on the VMAX chart correspond to the maximum of the sample variances of the two quality characteristics. The reason to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is the user's familiarity with the computation of simple sample variances; we can't say the same with regard to the computation of the generalized variance vertical bar S vertical bar.
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The T2 chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart) for monitoring the mean vector, sample variances (the VMAX chart) for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart) in the case of the joint control of the mean vector and the covariance matrix.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Technological advances and the availability of computational resources have been facilitating the collection and processing of data. Thus, the natural tendency of the monitoring processes is the simultaneous control of various quality characteristics. In automated processes, observations are generally autocorrelated. Studies with univariate graph for processes have shown that the autocorrelation reduces the ability of this signal changes in the process. In this paper, we study the multivariate autocorrelated processes. Through simulations are obtained properties of graphs, monitoring the mean vector, the properties of graphs VMAX, in monitoring the covariance matrix, and the properties of graphs MCMAX, the simultaneous monitoring of mean vector and covariance matrix. Conclude that increasing the autocorrelation and the number of variables being monitored, reduces the power of the graphics in signal of a special cause
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The possibility of kaon condensation in high-density symmetric nuclear matter is investigated including both s- and p-wave kaon-baryon interactions within the relativistic mean-field (RMF) theory. Above a certain density, we have a collective (D) over bar (S) state carrying the same quantum numbers as the antikaon. The appearance of the (K) over bar (S) state is caused by the time component of the axial-vector interaction between kaons and baryons. It is shown that the system becomes unstable with respect to condensation of K-(K) over bar (S) pairs. We consider how the effective baryon masses affect the kaon self-energy coming from the time component of the axial-vector interaction. Also, the role of the spatial component of the axial-vector interaction on the possible existence of the collective kaonic states is discussed in connection with A-mixing effects in the ground state of high-density matter: Implications of K (K) over bar (S) condensation for high-energy heavy-ion collisions are briefly mentioned. (c) 2005 Elsevier B.V. All rights reserved.
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Binding energy differences of mirror nuclei for A = 15, 17, 27, 29, 31, 33, 39 and 41 are calculated in the framework of relativistic deformed mean-field theory. To fully include the effects of the polarization of the nuclear core due to the extra particle or hole, the spatial components of the vector meson fields and the photon are taken into account in a self-consistent manner. The calculated binding energy differences are systematically smaller than the experimental values and lend support to the existency of the Okamoto-Nolen-Schiffer anomaly found decades ago in nonrelativistic calculations, For the majority of the nuclei studied, however, the results are such that the anomaly is significantly smaller than the one obtained within state-of-the-art nonrelativistic calculations.
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We use relativistic mean field theory, which includes scalar and vector mesons, to calculate the binding energy and charge radii in 125Cs - 139Cs. We then evaluate the nuclear structure corrections to the weak charges for a series of cesium isotopes using different parameters and estimate their uncertainty in the framework of this model.
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We analyze here the spin and pseudospin symmetry for the antinucleon spectra solving the Dirac equation with scalar and vector Wood-Saxon potentials. In relativistic nuclear mean field theories where these potentials have large magnitudes and opposite signs we show that contrary to the nucleon case where pseudospin interaction is never very small and cannot be treated perturbatively, for antinucleon systems this interaction is perturbative and an exact pseudospin symmetry is possible. This result manifests the relativistic nature of the nuclear pseudospin symmetry. © 2009 American Institute of Physics.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)