Confidence Balls in Gaussian Regression
نویسندگان
چکیده
where f = (f1, . . . , fn) ′ is an unknown vector, σ a positive number and ε1, . . . , εn a sequence of i.i.d. standard Gaussian random variables. For some β ∈ ]0,1[, the aim of this paper is to build a nonasymptotic Euclidean confidence ball for f with probability of coverage 1− β from the observation of Y = (Y1, . . . , Yn) ′. This statistical model includes, as a particular case, the functional regression model
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تاریخ انتشار 2004