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Generalized Semiaffine linear spaces
Ricerche di Matematica, 2016In this paper, the authors introduce the notion of ``generalized $T$-semiaffine spaces''. More precisely, let $T$ be a set of natural numbers, and let $S$ be a linear space admitting a finite dimension $n$ (many linear spaces do not admit a dimension) in the sense of \textit{F. Buekenhout} [J. Comb. Theory, Ser.
FERRARA DENTICE, Eva, Iannotta, Giusy
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Use generalized linear models or generalized partially linear models?
Statistics and Computing, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Xinmin +3 more
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MHD linear generator modelling
IEEE Transactions on Appiled Superconductivity, 1995The performance of typical magnetohydrodynamic (MHD) linear generators are evaluated as function of the excitation magnetic field profile. Using a three dimensional (3D) lumped parameter model, able to simulate all major physical MHD energy conversion phenomena, a parametric analysis has been pointed out for various saddle shaped superconducting (SC ...
GERI, Alberto +2 more
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Generating Linear Extensions Fast
SIAM Journal on Computing, 1994Summary: One of the most important sets associated with a poset \(\mathcal P\) is its set of linear extensions, \(E({\mathcal P})\). This paper presents an algorithm to generate all of the linear extensions of a poset in constant amortized time, that is, in time \(O(e({\mathcal P}))\), where \(e({\mathcal P})= | E({\mathcal P})|\).
Pruesse, Gara, Ruskey, Frank
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Generalized linear electrodynamics I
Acta Physica Academiae Scientiarum Hungaricae, 1957A generalized version ofPodolsky’s theory of higher order of the electromagnetic field is dealt with. The original field equations of higher order ofPodolsky’s theory is deduced from a new Lagrangian and the canonical formalism of the field, as well as the laws of conservation in the classical case are investigated.
Horvath, J. I., Vasvari, B.
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2007
This chapter presents the general linear model as an extension to the two-sample t-test, analysis of variance (ANOVA), and linear regression. We illustrate the general linear model using two-way ANOVA as a prime example. The underlying principle of ANOVA, which is based on the decomposition of the value of an observed variable into grand mean, group ...
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This chapter presents the general linear model as an extension to the two-sample t-test, analysis of variance (ANOVA), and linear regression. We illustrate the general linear model using two-way ANOVA as a prime example. The underlying principle of ANOVA, which is based on the decomposition of the value of an observed variable into grand mean, group ...
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Generalized piecewise linear histograms
Statistica Neerlandica, 2002We extend the concept of piecewise linear histogram introduced recently by Beirlant, Berlinet and Györfi. The disadvantage of that histogram is that in many models it takes on negative values with probability close to 1. We show that for a wide set of models, the extended class of estimates contains a bona fide density with probability tending to 1 as ...
Berlinet, A., Hobza, T., Vajda, I.
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GENERAL LINEAR DIFFERENCE SYSTEM
Analysis, 1999The author obtains a fundamental matrix of the following linear system \[ Y(x+1)= A(x)Y(x), \quad x\in E_{r_0} \tag{1} \] where \(E_{r_0}: =\{x\in \mathbb{C}\mid \text{Re} x\geq r_0\geq 2\}\), \(A(x)\) and \(Y(x)\) are \(m\times m\) matrices with entries in \(\mathbb{C}\), and \(A(x)\) is subject to some conditions.
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2015
This article provides an introduction into the statistical analysis of neuroimaging data using the general linear model. The analysis allows a flexible use of various models offering a wide range of statistical tests for the analysis of typical neuroimaging experiments. A short introduction to the general linear model is provided using simple examples.
Kiebel, S. +1 more
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This article provides an introduction into the statistical analysis of neuroimaging data using the general linear model. The analysis allows a flexible use of various models offering a wide range of statistical tests for the analysis of typical neuroimaging experiments. A short introduction to the general linear model is provided using simple examples.
Kiebel, S. +1 more
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Generalized Linear Complementarity Problems
Mathematics of Operations Research, 1995We introduce the concept of the generalized (monotone) linear complementarity problem (GLCP) in order to unify LP, convex QP, monotone LCP, and mixed monotone LCP. We establish the basic properties of GLCP and develop canonical forms for its representation. We show that the GLCP reduces to a monotone LCP in the same variables.
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