Resumo

SOSA, JUAN CAMILO  e  DIAZ, LUIS GUILLERMO. Random Time-Varying Coefficient Model Estimation through Radial Basis Functions. Rev.Colomb.Estad. [online]. 2012, vol.35, n.1, pp.167-184. ISSN 0120-1751.

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.

Palavras-chave : Cross validation; Kernel function; Longitudinal data analysis; Mixed model.

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