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- W2077161011 abstract "We present rates of convergence for (penalized or sieved) M-estimators of a parameter in a normed vector space, using a loss function that is convex in the parameter. We show how the convexity can be used to ‘localize’ the problem, i.e., to confine considerations to a small neighborhood in parameter space. The results are then along the lines as those for the least squares problem: rates follow from entropy calculations (on that small neighborhood). As detailed example, we consider the estimation of a log-density." @default.
- W2077161011 created "2016-06-24" @default.
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- W2077161011 date "2002-11-01" @default.
- W2077161011 modified "2023-10-16" @default.
- W2077161011 title "M-estimation using penalties or sieves" @default.
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- W2077161011 doi "https://doi.org/10.1016/s0378-3758(02)00270-7" @default.
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