نتایج جستجو برای: mixed model u

تعداد نتایج: 2413611  

2017
Sergio I. Quiroz Marzena Zygis

This paper investigates calling melodies produced by 21 Standard German native speakers on a discourse completion task across two contexts: (i) routine context—calling a child from afar to come in for dinner; (ii) urgent context—calling a child from afar for a chastising. The intent of this investigation is to bring attention to other calling melodies found in German beside the vocative chant a...

2005
Heping Zhang

In this document, we introduce five additional examples that motivate our research on testing homogeneity. In particular, we show how to check the assumptions for two linear mixed models to validate the asymptotic distributions of the score test statistics. Then, we give the detailed derivation for the score test statistic. We present the result about the local power of the score test statistic...

2013
Jinfeng Wang Hong Li Siriguleng He Wei Gao Yang Liu

We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to...

2006
J. T. ODEN

The idea of conjugate or dual representations for finite-element approximations was introduced in [1] in connection with purely topological properties of finite element models; i.e., in the spirit of linear graph theory, if f(u) is a linear functional on a space M of finite element approximations u, then there exists a consistent (conjugate) approximation of f which renders f(u) invariant under...

2012
E. Kwessi A. Abebe G. De Souza

We provide an estimate of the score function for rank regression using compactly supported wavelets. This estimate is then used to find a rank-based asymptotically efficient estimator for the slope parameter of a linear model. We also provide a consistent estimator of the asymptotic variance of the rank estimator. For related mixed models, the asymptotic relative efficiency is also discussed

2009
Brian Batell

A secluded U(1)S gauge field, kinetically mixed with Standard Model hypercharge, provides a ‘portal’ mediating interactions with a hidden sector at the renormalizable level, as recently exploited in the context of WIMP dark matter. The U(1)S symmetry-breaking scale may naturally be suppressed relative to the weak scale, and so this sector is efficiently probed by medium energy ee colliders. We ...

Journal: :Statistics and Computing 2011
Ruggero Bellio Alessandra R. Brazzale

Journal: :Statistics and Computing 2012
Hossein Baghishani Håvard Rue Mohsen Mohammadzadeh

Data cloning method is a new computational tool for computing maximum likelihood estimates in complex statistical models such as mixed models. The data cloning method is synthesized with integrated nested Laplace approximation to compute maximum likelihood estimates efficiently via a fast implementation in generalized linear mixed models. Asymptotic normality of the hybrid data cloning based di...

2004
Thomas Kneib Stefan Lang Andreas Brezger

This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression models based on mixed model methodology. As an example we consider data on undernutrition of children in Zambia. The tutorial is designed to be self-contained and describes all features of BayesX in detail, that will be needed throughout the tutorial. Therefore it may also serve as a first introducti...

2006
Bhaskar Dutta Jason Kumar

We introduce a novel mechanism for baryogenesis, in which mixed anomalies between the hidden sector and U(1)baryon drive the baryon asymmetry. We demonstrate that this mechanism occurs quite naturally in intersecting-brane constructions of the Standard Model, and show that it solves some of the theoretical difficulties faced in matching baryogenesis to experimental bounds. We illustrate with a ...

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