TITLE

Development of Admire Longitudinal Quasi-Linear Model by using State Transformation Approach

AUTHOR(S)
Yu Jianqiao; Wang Jianbo; He Xinzhen
PUB. DATE
August 2010
SOURCE
World Academy of Science, Engineering & Technology;Aug2010, Issue 44, p1414
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
No abstract available.
ACCESSION #
60741600

 

Related Articles

  • LINEAR MODEL FOR A DUAL DISTRIBUTION THERMODYNAMIC SYSTEM. Pop, Mihail-Ioan // Bulletin of the Transilvania University of Brasov, Series III: M;2008, Vol. 1 Issue 50, p559 

    We consider the case of a thermodynamic system that may have two possible distributions at any time. A linear combination of the two distributions is proposed for the observed distribution of the system. A brief mathematical analysis is given. The thermodynamic parameters of the system are...

  • A comparison of methods for estimating the random effects distribution of a linear mixed model. Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert // Statistical Methods in Medical Research;Dec2010, Vol. 19 Issue 6, p575 

    This article reviews various recently suggested approaches to estimate the random effects distribution in a linear mixed model, i.e. (1) the smoothing by roughening approach of Shen and Louis,1 (2) the semi-non-parametric approach of Zhang and Davidian,2 (3) the heterogeneity model of Verbeke...

  • APPLICATION OF RESULTS OF EXPERIMENTAL IDENTIFICATION IN CONTROL OF LABORATORY HELICOPTER MODEL. Dolinsky, Kamil; Jadlovska, Anna // Advances in Electrical & Electronic Engineering;Dec2011, Vol. 9 Issue 4, p157 

    This article deals with experimental identification and control of laboratory helicopter model CE 150 manufactured by company Humusoft. Structure of the identified system was approximated by linear black-box models. Discrete Input/Output Auto-Regressive Moving Average model with eXternal input...

  • A Spatial Stochastic Model for Virus Dynamics. Schinazi, Rinaldo // Journal of Statistical Physics;Aug2007, Vol. 128 Issue 3, p771 

    We introduce a spatial stochastic model for virus dynamics. We show that if the death rate of infected cells increases too fast with the virus load the virus dies out. This is in sharp contrast with what happens in the (non-spatial deterministic) basic model for virus dynamics.

  • A mixed-integer model for solving ordering problems with side constraints. Maffioli, Francesco; Sciomachen, Anna // Annals of Operations Research;1997, Vol. 69 Issue 1-4, p277 

    We present an exact approach for solving the Sequential Ordering Problem (SOP). In this problem, a set of jobs has to be processed on a single machine; a time window (deadline-release date) is associated with each job, and precedence relationships between jobs are given. Moreover, a setup time...

  • Numerical simulation of bidisperse granular material flow in a rotating reactor. Dorofeenko, S. O.; Polianczyk, E. V.; Manelis, G. B. // Doklady Physics;Oct2008, Vol. 53 Issue 10, p510 

    The article discusses the probe of bidisperse behavioral flow of granular media in a tilted rotating reactor through simulation. It says that the medium was under the action of gravity and uses the discrete element method. Moreover, elastic deformation, energy dissipation, and friction are...

  • On the robustness of the adaptive lasso to model misspecification. Lu, W.; Goldberg, Y.; Fine, J. P. // Biometrika;Sep2012, Vol. 99 Issue 3, p717 

    Penalization methods have been shown to yield both consistent variable selection and oracle parameter estimation under correct model specification. In this article, we study such methods under model misspecification, where the assumed form of the regression function is incorrect, including...

  • Matlab7.0.4/Simulink ile Aksonun Pasif Kablo Modellemesi ve Simülasyonu.  // Pamukkale University Journal of Engineering Sciences;2010, Vol. 16 Issue 3, p283 

    No abstract available.

  • Estimating overdispersion when fitting a generalized linear model to sparse data. Fletcher, D. J. // Biometrika;Mar2012, Vol. 99 Issue 1, p230 

    We consider the problem of fitting a generalized linear model to overdispersed data, focussing on a quasilikelihood approach in which the variance is assumed to be proportional to that specified by the model, and the constant of proportionality, φ, is used to obtain appropriate standard...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics