试探算法与SSOR预处理共轭梯度算法的拟最佳因子

1引言在求解系数矩阵为对称正定的大型线性代数方程组Au=b (1．1)的迭代法方面,七十年代以来发展了各种预处理共轭梯度法．由于SSOR分裂中具有对称因子,可用于加速共轭梯度法,称为SSOR预处理共轭梯度法(简记为;SSORPCG．同时,由于当松弛因子ω∈(0,2)时,SSOR迭代法收敛,从而进一步发展了m步SSOR预处理共轭梯度法(简记为:m-step SSORPCG．胡家赣证明,经过最优的SSOR预条件,预优     

Weibull分布场合具有非常数形状参数恒加试验的参数估计

本文讨论了Weibull分布场合恒加寿命试验的点估计和近似区间估计，利用模拟方法说明所给方法的有效性。     

Simultaneous recording of fringe patterns with one camera

A novel method to separate and simultaneously record the Moiré interferometry fringe patterns of three deformation fields with only one CCD camera is developed; details of its operation principle, key points and error analysis are presented. With this technique, the deformation inU, V andW fields can be measured simultaneously, so dynamic test with comprehensive information can be performed. The advantage of this technique over other similar techniques lies in its simplicity, easy implementation and low cost. An application of this technique is given to show its feasibility. Technical problems that may be caused with this technique are also analyzed.     

Confidence Regions on Variance Components in an Extended ANOVA Model for Combining Information

In this paper we consider a general variance components model for combining experiments that allows for a possible interaction of responses with groups. The variance estimate from each experiment cannot take into account this interaction which can additionally be different from experiment to experiment. The interaction term can be interpreted as an additional variance component so that we consider an extended ANOVA model. We derive confidence regions and test of hypotheses on the variance components which – at least approximately – hold the nominal significance level.     

Brent原油期货市场的协整性分析

本文利用单位根检验和协整关系检验验证了Brent原油期货市场的有效范围,发现其在5个月内是有效的。在市场有效范围内,对现货价格和期货价格建立了向量误差修正模型,具有良好的预测效果。同时发现该期货市场某时刻价格的影响可以持续2个月。     

Testing for Mean Reversion in Processes of Ornstein-Uhlenbeck Type

In this paper, we analyse processes of Ornstein-Uhlenbeck (OU) type, driven by Lévy processes. This class is designed to capture mean reverting behaviour if it exists; but the data may in fact be adequately described by a pure Lévy process with no OU (autoregressive) effect. For an appropriate discretised version of the model, we utilise likelihood methods to test for such a reduction of the OU process to Lévy motion, deriving the distribution of the relevant pseudo-log-likelihood ratio statistics, asymptotically, both for a refining sequence of partitions on a fixed time interval with mesh size tending to zero, and as the length of the observation window grows large. These analyses are non-standard in that the mean reversion parameter vanishes under the null of a pure Lévy process for the data. Despite this we are able to give a very general analysis with no technical restrictions on the underlying processes or parameter sets, other than a finite variance assumption for the Lévy process. As a special case, for Brownian motion as driving process, we deduce the limiting distribution in a quite explicit way, finding results which generalise the well-known Dickey-Fuller (‘unit-root’) theory. This revised version was published online in June 2006 with corrections to the Cover Date.     

DIMENSION-REDUCTION TYPE TESTFOR LINEARITY OF ASTOCHASTIC REGRESSION MODEL

1.IntroductionLinearregressionmodelsarewidelyusedinstatisticalanalysisofexperimentalandobservationaldata,thatis,oneoftenemploysastandardlinearmodely=or K: E,a.s.,(1.1)todostatisticalanalysis,whereydenotesascalaroutcomevariableand2denotesaP-dimensionalcolumnvectorofregressorvariables.Thismodelmeansthattheprojectionofthepdimensionalexplanatory2ontotheone-dimensionalsubspaceadZcapturesalltheinformationweneedtoknowabouttheoutcomevariabley.Thisisadimension-reductionmodel.Hencewemayreachthegoalofd…     

Weibull分布损伤失效率模型常应力下的参数估计

Bhattacharyya和Soejoeti(1989)对步进应力加速寿命试验提出损伤失效率模型(TFR模型)．本文在全加速步加试验场合下指出文献[1]，[2]，[5]中用通常的回归分析方法求取常应力下参数的估计是不合理的，同时给出了如何求取常应力下参数估计的一种方法．     

Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model

This paper is concerned with the null distribution of test statistic T for testing a linear hypothesis in a linear model without assuming normal errors. The test statistic includes typical ANOVA test statistics. It is known that the null distribution of T converges to χ² when the sample size n is large under an adequate condition of the design matrix. We extend this result by obtaining an asymptotic expansion under general condition. Next, asymptotic expansions of one- and two-way test statistics are obtained by using this general one. Numerical accuracies are studied for some approximations of percent points and actual test sizes of T for two-way ANOVA test case based on the limiting distribution and an asymptotic expansion.     

Admissibility of unbiased tests for a composite hypothesis with a restricted alternative

This paper discusses -admissiblility and d-admissiblity which are important concepts in studying the performance of statistical tests for composite hypotheses. A sufficient condition for -admissibility is presented. When =1/m, the Nomakuchi-Sakata test, which is uniformly more powerful than the likelihood ratio test for hypotheses min (₁, ₁) = 0 versus min (₁, ₁) > 0, is generalized for a class of distributions in an exponential family, and its unbiasedness and -admissibility are shown. Finally, the case of 1/m is discussed in brief.