SPLINE FUNCTIONS AND STOCHASTIC FILTERING

成果类型:
Article
署名作者:
THOMASAGNAN, C
署名单位:
Universite de Toulouse; Universite Toulouse 1 Capitole
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
DOI:
10.1214/aos/1176348259
发表日期:
1991
页码:
1512-1527
关键词:
cross validation
摘要:
Some relationships have been established between unbiased linear predictors of processes, in signal and noise models, minimizing the predictive mean square error and some smoothing spline functions. We construct a new family of multidimensional splines adapted to the prediction of locally homogeneous random fields, whose m-spectral measure (to be defined) is absolutely continuous with respect to Lebesgue measure and satisfies some minor assumptions. By considering partial splines, one may include an arbitrary drift in the signal. This type of correspondence underlines the potentialities of cross-fertilization between statistics and the numerical techniques in approximation theory.