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91.
The best-r-point-average (BRPA) estimator of the maximizer of a regression function, proposed in Changchien (in: M.T. Chao, P.E. Cheng (Eds.), Proceedings of the 1990 Taipei Symposium in Statistics, June 28–30, 1990, pp. 63–78) has certain merits over the estimators derived through the estimation of the regression function. Some of the properties of the BRPA estimator have been studied in Chen et al. (J. Multivariate Anal. 57 (1996) 191) and Bai and Huang (Sankhya: Indian J. Statist. Ser. A. 61 (Pt. 2) (1999) 208–217). In this article, we further study the properties of the BRPA estimator and give its convergence rate under some quite general conditions. Simulation results are presented for the illustration of the convergence rate. Some comparisons with existing estimators such as the Müller estimator are provided. 相似文献
92.
93.
Stefan Jaschke Claudia Klüppelberg Alexander Lindner 《Journal of multivariate analysis》2004,88(2):252-273
We derive results on the asymptotic behavior of tails and quantiles of quadratic forms of Gaussian vectors. They appear in particular in delta–gamma models in financial risk management approximating portfolio returns. Quantile estimation corresponds to the estimation of the Value-at-Risk, which is a serious problem in high dimension. 相似文献
94.
95.
Framstad N. C. Øksendal B. Sulem A. 《Journal of Optimization Theory and Applications》2004,121(1):77-98
We give a verification theorem by employing Arrow's generalization of the Mangasarian sufficient condition to a general jump diffusion setting and show the connections of adjoint processes to dynamic programming. The result is applied to financial optimization problems. 相似文献
96.
This paper considers the estimation problem for a trigonometric regression model with the noise specified by the Ornstein–Uhlenbeck
process with unknown parameter. We propose a sequential procedure which ensures a prescribed mean square precision uniformly
in the nuisance parameter. The asymptotic behaviour of the procedure duration mean has been studied.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
97.
This paper investigates regression quantiles (RQ) for unstable autoregressive models. The uniform Bahadur representation of the RQ process is obtained. The joint asymptotic distribution of the RQ process is derived in a unified manner for all types of characteristic roots on or outside the unit circle. It involves stochastic integrals in terms of a sequence of independent and identically distributed multivariate Brownian motions with correlated components. The related L-estimator is also discussed. The asymptotic distributions of the RQ and the L-estimator corresponding to the nonstationary componentwise arguments can be transformed into a function of a normal random variable and a sequence of i.i.d. univariate Brownian motions. This is different from the analysis based on the LSE in the literature. As an auxiliary theorem, a weak convergence of a randomly weighted residual empirical process to the stochastic integral of a Kiefer process is established. The results obtained in this paper provide an asymptotic theory for nonstationary time series processes, which can be used to construct robust unit root tests. 相似文献
98.
The aim of this paper is to present two different approachs in order to obtain an existence result to the so-called quadrature
surface free boundary problem. The first one requires the shape derivative calculus while the second one depends strongly
on the compatibility condition of the Neumann problem. A necessary and sufficient condition of existences is given in the
radial case. 相似文献
99.
In this paper we consider the problem of estimating an unknown joint distribution which is defined over mixed discrete and continuous variables. A nonparametric kernel approach is proposed with smoothing parameters obtained from the cross-validated minimization of the estimator's integrated squared error. We derive the rate of convergence of the cross-validated smoothing parameters to their ‘benchmark’ optimal values, and we also establish the asymptotic normality of the resulting nonparametric kernel density estimator. Monte Carlo simulations illustrate that the proposed estimator performs substantially better than the conventional nonparametric frequency estimator in a range of settings. The simulations also demonstrate that the proposed approach does not suffer from known limitations of the likelihood cross-validation method which breaks down with commonly used kernels when the continuous variables are drawn from fat-tailed distributions. An empirical application demonstrates that the proposed method can yield superior predictions relative to commonly used parametric models. 相似文献
100.
高阶非线性波动方程的有限差分方法 总被引:2,自引:0,他引:2
本文研究一类广泛的高阶非线性波动方程组初边值问题的有限差分格式,用离散泛函分析方法和先验估计的技巧得到了有限差分格式的收敛性。 相似文献