Statistical Methods for Dynamic Models with Application - Tapa blanda

Lu, Tao

 
9783659537103: Statistical Methods for Dynamic Models with Application
Tapa blanda
ISBN 10: 3659537101 ISBN 13: 9783659537103
Editorial: LAP LAMBERT Academic Publishing, 2016

Sinopsis

Recent outbreak of Human Influenza A H1N1 virus infection commands statistics playing an important role on guidance of prevention and treatment. Viral Dynamic Model, a set of ordinary differential equations (ODE) which describes interaction between virus and the immune system, has been proved useful in understanding the pathogenesis of virus infection and developing treatment strategy for many viral infection diseases, such as HIV, HCV, HBV and so on. In order to estimate biological/clinical meaningful parameters in various dynamic models, many statistical approaches have been developed in the last decade, from simple nonlinear least square (NLS) approach to more general nonlinear Mixed-effect modeling approach. However, for a general nonlinear ODE model, no close form solution is available and it has to be solved numerically. In such a situation, a general approach has to be developed to deal with this complexity. Two iomarkers, viral load and number of immune cells, are critical data source for dynamical models.

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Reseña del editor

Recent outbreak of Human Influenza A H1N1 virus infection commands statistics playing an important role on guidance of prevention and treatment. Viral Dynamic Model, a set of ordinary differential equations (ODE) which describes interaction between virus and the immune system, has been proved useful in understanding the pathogenesis of virus infection and developing treatment strategy for many viral infection diseases, such as HIV, HCV, HBV and so on. In order to estimate biological/clinical meaningful parameters in various dynamic models, many statistical approaches have been developed in the last decade, from simple nonlinear least square (NLS) approach to more general nonlinear Mixed-effect modeling approach. However, for a general nonlinear ODE model, no close form solution is available and it has to be solved numerically. In such a situation, a general approach has to be developed to deal with this complexity. Two iomarkers, viral load and number of immune cells, are critical data source for dynamical models.

Biografía del autor

Dr. Lu is an expert in longitudinal data analysis, dynamic network modeling and Bayesian modeling. He has developed various statistical methods and applied them to infectious disease modeling and other dynamic processes. He has published many articles in prestigious journals such as Journal of the American Statistical Association and Biometrics.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2016
Idioma
Inglés
ISBN 10 
3659537101
ISBN 13 
9783659537103
Encuadernación
Tapa blanda
Número de páginas
100
Contacto del fabricante
no disponible
Persona responsable
no disponible