Maximum Likelihood Estimation with Stata, Third Edition - Tapa blanda

Sribney, William

 
9781597180122: Maximum Likelihood Estimation with Stata, Third Edition
Tapa blanda
ISBN 10: 1597180122 ISBN 13: 9781597180122
Editorial: Stata Press, 2005

Sinopsis

Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions.

New ml commands and their functions:

  • constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix
  • ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data
  • optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS)
  • ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)

    • "Sinopsis" puede pertenecer a otra edición de este libro.

    Reseña del editor

    Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions.

    New ml commands and their functions:

  • constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix
  • ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data
  • optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS)
  • ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)

    • "Sobre este título" puede pertenecer a otra edición de este libro.

    Editorial
    Stata Press
    Año de publicación
    2005
    Idioma
    Inglés
    ISBN 10 
    1597180122
    ISBN 13 
    9781597180122
    Encuadernación
    Tapa blanda
    Número de edición
    3
    Número de páginas
    290
    Contacto del fabricante
    no disponible
    Persona responsable
    no disponible