On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

约束优化问题的异步并行拟牛顿方法

提出了一种求解等式约束优化问题的异步并行拟牛顿方法 .若假设目标函数 f和约束函数h至少三次连续可微 ,且△h(x)对任意x∈Rn 均为满秩矩阵 ,证明了所提出的异步并行算法是 q—超线性收敛的 .     

Deconvolution with supersmooth distributions

Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted L_p-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented.     

On Rates of Convergence for Bayesian Density Estimation

Abstract.  We consider the problem of estimating a compactly supported density taking a Bayesian nonparametric approach. We define a Dirichlet mixture prior that, while selecting piecewise constant densities, has full support on the Hellinger metric space of all commonly dominated probability measures on a known bounded interval. We derive pointwise rates of convergence for the posterior expected density by studying the speed at which the posterior mass accumulates on shrinking Hellinger neighbourhoods of the sampling density. If the data are sampled from a strictly positive, α -Hölderian density, with α  ∈ ( 0,1] , then the optimal convergence rate n^{− α / (2 α +1)} is obtained up to a logarithmic factor. Smoothing histograms by polygons, a continuous piecewise linear estimator is obtained that for twice continuously differentiable, strictly positive densities satisfying boundary conditions attains a rate comparable up to a logarithmic factor to the convergence rate n ^−4/5 for integrated mean squared error of kernel type density estimators.     

块Jacobi迭代阵的收敛性

研究大型线性方程组迭代解法中分块ＪＡＣＯＢＩ迭代阵的收敛性。采用块矩阵分析方法和谱半径降维估计法得到块Ｊａｃｏｂｉ迭代阵收敛的实用充分条件。     

经济收敛理论与检验方法研究综述

在大量文献研究的基础上,对收敛问题的产生及收敛概念的发展作了全面概括,并对绝对收敛、条件收敛、俱乐部收敛和σ收敛作了深入辨析,对各种识别方法作了全面归纳。归纳了对世界大多数国家和地区数据所作识别的结果。还从收敛理论与传统理论的冲突与协调方面作了深入分析。最后对近年收敛研究的深化与扩展研究的趋势作了概括。     

服务产品价格的范围与振荡收敛性研究

服务提供商占有服务创造的价值的问题必然涉及到对服务产品的定价。通过使用价格和服务量共同来描述服务价值的创造与分配,用服务产品的价格的确定来实现价值的分配,用不同的价格决定权和博弈顺序来确定服务产品的价格范围,然后寻求一种服务产品价格的振荡系统,使得服务产品的价格最终收敛于总价值创造最高的价格。     

Standard errors for EM estimation

The EM algorithm is a popular method for computing maximum likelihood estimates. One of its drawbacks is that it does not produce standard errors as a by-product. We consider obtaining standard errors by numerical differentiation. Two approaches are considered. The first differentiates the Fisher score vector to yield the Hessian of the log-likelihood. The second differentiates the EM operator and uses an identity that relates its derivative to the Hessian of the log-likelihood. The well-known SEM algorithm uses the second approach. We consider three additional algorithms: one that uses the first approach and two that use the second. We evaluate the complexity and precision of these three and the SEM in algorithm seven examples. The first is a single-parameter example used to give insight. The others are three examples in each of two areas of EM application: Poisson mixture models and the estimation of covariance from incomplete data. The examples show that there are algorithms that are much simpler and more accurate than the SEM algorithm. Hopefully their simplicity will increase the availability of standard error estimates in EM applications. It is shown that, as previously conjectured, a symmetry diagnostic can accurately estimate errors arising from numerical differentiation. Some issues related to the speed of the EM algorithm and algorithms that differentiate the EM operator are identified.     

Asymptotic Bias in Parameter Estimation of AR-Processes Using Recursive Least Squares with Exponential Forgetting

The recursive least squares technique is often extended with exponential forgetting as a tool for parameter estimation in time-varying systems. The distribution of the resulting parameter estimates is, however, unknown when the forgetting factor is less than one. In this paper an approximative expression for bias of the recursively obtained parameter estimates in a time-invariant AR( n_a ) process with arbitrary noise is given, showing that the bias is non-zero and giving bounds on the approximation errors. Simulations confirm the approximation expressions.     

城市群可持续发展水平演化及其影响因素研究——来自中国十大城市群的证据

采用基于变异系数的灰色关联分析方法,度量2002-2011年中国十大城市群可持续发展水平并分析其收敛性和影响因素。研究发现:十大城市群在经济发展水平、社会进步程度、生态环境状况、资源供给能力方面呈现显著的差异,城市群可持续发展水平并没有与经济增长的大趋势保持一致;城市群可持续发展水平收敛特征具有分区域特点,全国样本具有非绝对收敛但条件收敛的特征,东部地区城市群绝对收敛特征不显著,但条件收敛特征较明显,而中部与西部城市群具有绝对收敛和条件收敛特征;经济发展水平、社会进步程度等变量与城市群可持续发展水平之间正向相关,但其影响程度在不同区域具有显著差异。