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非参数回归、置信区域与正则化AI 解读

In this paper we offer a unified approach to the problem of nonparametric regression on the unit interval. It is based on a universal, honest and nonasymptotic confidence region $\mathcal{A}_{n}$ which is defined by a set of linear inequalities involving the values of the functions at the design points. Interest will typically center on certain simplest functions in $\mathcal{A}_{n}$ where simplicity can be defined in terms of shape (number of local extremes, intervals of…

稳健线性回归的若干问题AI 解读

Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact Holder condition of order 1/2 at models with normal errors. In Section 5 the breakdown points of the Hampel-Krasker dispersion and regression functionals are shown to be 0. The…

最小协方差行列式估计量的渐近性质AI 解读

Consistency is shown for the minimum covariance determinant (MCD) estimators of multivariate location and scale and asymptotic normality is shown for the former. The proofs are made possible by showing a separating ellipsoid property for the MCD subset of observations. An analogous property is shown for the MCD subset computed from the population distribution.

多元位置参数与离散矩阵 S 估计的渐近行为AI 解读

It is shown under appropriate conditions that Rousseeuw's minimum volume estimator and other $S$-estimators of multivariate location and dispersion parameters are consistent. Under certain differentiability conditions the estimates are asymptotically normally distributed with a norming factor of $n^{1/2}$.