988 resultados para TAYLOR SERIES EXPANSION


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A photograph of the Taylor family with Robert Band as they celebrate Christmas. There are four adults and three children all in front of a Christmas tree.

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A new series of nano-sized Ce1-xEuxCrO3 (x = 0.0 to 1.0) with an average particle size of 50 - 80 nm were synthesized using a solution combustion method. Nano-powders Ce1-xEuxCrO3 with the canted antiferromagnetic property exhibited interesting magnetic behaviours including the reversal magnetization and the exchange bias effect. The effect of europium doping as the ion with the smaller radius size and different electron con figuration on structural, magnetic and thermal properties of Ce1-xEuxCrO3 were investigated using various experimental techniques, i.e. DC/AC magnetic susceptibility, heat capacity, thermal expansion, Raman scattering, X-ray photoemission spectroscopy, transmission/scanning electron microscopy, X-ray powder diffraction and neutron scattering. An exchange bias effect, magnetization irreversibility and AC susceptibility dispersion in these samples confirmed the existence of the spin disorder magnetic phase in Ce1-xEuxCrO3 compounds. The exchange bias phenomenon, which is assigned to the exchange coupling between glassy-like shell and canted antiferromagnetic core, showed the opposite sign in CeCrO3 and EuCrO3 at low temperatures, suggesting different exchange interactions at the interfaces in these compounds. The energy level excitation of samples were examined by an inelastic neutron scattering which was in good agreement with the heat capacity data. Neutron scattering analysis of EuCrO3 was challenging due to the large neutron absorption cross-section of europium. All diffraction patterns of Ce1-xEuxCrO3 showed the magnetic peak attributed to the antiferromagnetic Cr3+ spins while none of the diffraction patterns could detect the magnetic ordering of the rare-earth ions in these samples.

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Receipt from Taylor and Bowley Licensees, Charing Cross London for 1 set of hollow shoe trees, April 26, 1847.

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Tesis (Maestro en ciencias de la ingeniería eléctrica con especialidad en potencia) U.A.N.L. Facultad de Ingeniería Mecánica y Eléctrica.

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Tesis (Maestro en Ciencias de la Ingeniería Eléctrica con Orientación en Sistemas Eléctricos de Potencia) UANL, 2011.

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Tesis (Maestría en Ciencias con Orientación en Matemáticas) UANL, 2013.

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This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

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We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses considered are nonlinear, the proposed methods only require linear regression techniques as well as standard Gaussian asymptotic distributional theory. Bootstrap procedures are also considered. For the case of integrated processes, we propose extended regression methods that avoid nonstandard asymptotics. The methods are applied to a VAR model of the U.S. economy.

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We consider the problem of testing whether the observations X1, ..., Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed: exponential bounds, Eaton-type bounds, Chebyshev bounds and Berry-Esséen-Zolotarev bounds. The bounds are exact in finite samples, distribution-free and easy to compute. The performance of the bounds is evaluated and compared with traditional serial dependence tests in a simulation experiment. The procedures proposed are applied to U.S. data on interest rates (commercial paper rate).

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