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2012-01-01
ESTIMACIÓN DE LOS COEFICIENTES DE UN MODELO DE COEFICIENTES DINÁMICOS Y ALEATORIOS A TRAVÉS DE FUNCIONES RADIALES KERNEL
RANDOM TIME-VARYING COEFFICIENT MODEL ESTIMATION THROUGH RADIAL BASIS FUNCTIONS
Keywords:
análisis de datos longitudinales, función kernel, modelo mixto, validación cruzada (es)Cross validation, Kernel function, Longitudinal data analysis, Mixed model (en)
Se propone una metodología para estimar los coeficientes de un modelo de coeficientes dinámicos y aleatorios a través de una combinación lineal de funciones radiales kernel centradas en los diferentes puntos de medición, o en cuantiles de éstos, escalada por un ancho de banda que puede cambiar de coeficiente a coeficiente. En un estudio de simulación se compara la metodología propuesta con la estimación mediante los métodos de polinomios locales kernel, obteniéndose que la nueva metodología propuesta es la mejor opción en un alto porcentaje de veces para todos los escenarios simulados, o por lo menos se desempeña similarmente a la estimación a través de la regresión de polinomios locales kernel, que pocas veces se desempeña mejor que la estimación mediante funciones radiales kernel, en relación al error cuadrático medio promedio. Para ilustrar la estrategia de estimación propuesta se considera el conjunto de datos ACTG 315 asociado con un estudio del SIDA, en el que se modela dinámicamente la relación entre la carga viral y el conteo de células CD4+.
A methodology to estimate a time-varying coefficient model through a linear combination of radial kernel functions which are centered around all the measuring times, or their quantiles is developed. The linear combination is weighted by a bandwidth that may change or not among coefficients. The proposed methodology is compared with the local polynomial kernel methods by means of a simulation study. The proposed methodology shows a better behavior in a high proportion of times in all cases, or at least it has a similar behavior in relation with the estimation through local polynomial kernel regression, that in a low rate of times has a better behavior in relation with the average mean square error. In order to illustrate the methodology the data set ACTG 315 related with an AIDS study is taken into account. The dynamic relationship between the viral load and the CD4+ cell counts is investigated.
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