953 resultados para quasi-likelihood
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Cover title.
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Mode of access: Internet.
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"The impression for sale is one hundred copies folio and seven hundred and fifty copies quarto.
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Mode of access: Internet.
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"November 1982."
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Contiene además: "Principis Federici Caesii ... De caeli vnitate, tenvitate, fusaque & peruia stellarum motibus natura ... ad ... Robertum Bellarminum ... epistola": pp. [775]-784
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Bibliography: leaves 16-17.
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Mode of access: Internet.
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Mode of access: Internet.
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Bibliography: p. 77-83.
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In simultaneous analyses of multiple data partitions, the trees relevant when measuring support for a clade are the optimal tree, and the best tree lacking the clade (i.e., the most reasonable alternative). The parsimony-based method of partitioned branch support (PBS) forces each data set to arbitrate between the two relevant trees. This value is the amount each data set contributes to clade support in the combined analysis, and can be very different to support apparent in separate analyses. The approach used in PBS can also be employed in likelihood: a simultaneous analysis of all data retrieves the maximum likelihood tree, and the best tree without the clade of interest is also found. Each data set is fitted to the two trees and the log-likelihood difference calculated, giving partitioned likelihood support (PLS) for each data set. These calculations can be performed regardless of the complexity of the ML model adopted. The significance of PLS can be evaluated using a variety of resampling methods, such as the Kishino-Hasegawa test, the Shimodiara-Hasegawa test, or likelihood weights, although the appropriateness and assumptions of these tests remains debated.
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We present a novel method, called the transform likelihood ratio (TLR) method, for estimation of rare event probabilities with heavy-tailed distributions. Via a simple transformation ( change of variables) technique the TLR method reduces the original rare event probability estimation with heavy tail distributions to an equivalent one with light tail distributions. Once this transformation has been established we estimate the rare event probability via importance sampling, using the classical exponential change of measure or the standard likelihood ratio change of measure. In the latter case the importance sampling distribution is chosen from the same parametric family as the transformed distribution. We estimate the optimal parameter vector of the importance sampling distribution using the cross-entropy method. We prove the polynomial complexity of the TLR method for certain heavy-tailed models and demonstrate numerically its high efficiency for various heavy-tailed models previously thought to be intractable. We also show that the TLR method can be viewed as a universal tool in the sense that not only it provides a unified view for heavy-tailed simulation but also can be efficiently used in simulation with light-tailed distributions. We present extensive simulation results which support the efficiency of the TLR method.
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In diagnosis and prognosis, we should avoid intuitive “guesstimates” and seek a validated numerical aid
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The design of an X-band tray-type spatial power combiner, which employs uniplanar quasi-Yagi antennas (QYAs) for receiving and transmitting signals by individual amplifiers, is presented. Passive and active varieties of a seven-tray power-combining structure that includes two hard horns for uniform signal launching and combining across the tray stack are developed and measured. In order to compensate for nonuniform phase across the stack, which is caused by the nonplanar wave front of the horn antennas, Schiffman phase shifters are implemented in individual trays. The experimental-results show an improved performance of the investigated tray-type power combiner when the proposed phase-error compensation is implemented. (C) 2004 Wiley Periodicals, Inc.