Confidence balls in Gaussian regression
Baraud, Yannick
HAL, hal-00012909 / Harvested from HAL
Text on HAL
Starting from the observation of an R^n-Gaussian vector of mean f and covariance matrix \\sigma^2 I_n (I_n is the identity matrix), we propose a method for building a Euclidean confidence ball around f, with prescribed probability of coverage. For each n, we describe its nonasymptotic property and show its optimality with respect to some criteria.
Publié le : 2004-07-05
Classification:  [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] 
@article{hal-00012909,
     author = {Baraud, Yannick},
     title = {Confidence balls in Gaussian regression},
     journal = {HAL},
     volume = {2004},
     number = {0},
     year = {2004},
     language = {en},
     url = {http://dml.mathdoc.fr/item/hal-00012909}
}

Baraud, Yannick. Confidence balls in Gaussian regression. HAL, Tome 2004 (2004) no. 0, . http://gdmltest.u-ga.fr/item/hal-00012909/