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将二维序贯均匀设计方法拓展到三维空间,扩展到三维的序贯均匀设计可用于优化的三因子试验设计问题,从而达到既减少试验次数,又提高试验精度的目的. 相似文献
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评估置信区间的两个常用准则为区间宽度与覆盖率,研究同时达到给定的区间长度与名义覆盖率的区间估计在实际应用中有重要的价值,但这在固定样本量的情况下是无法实现的.应用序贯方法和两阶段抽样方法,乃至多阶段抽样方法是解决这一问题的常用途径.本文对零膨胀泊松分布的两个参数,取零概率p和泊松均值参数λ,进行了固定宽度置信区间的序贯方法和两阶段方法的研究,证明了所提出的所有序贯过程与两阶段过程的渐近相合性与有效性,并通过蒙特卡罗模拟研究展示了所提出方法的效果,并考虑了不同情况下最优固定样本量随两个参数的变化趋势,并通过实证分析来说明方法的应用价值. 相似文献
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本文应用数论方法解决一个实际中遇到的单位圆的覆盖问题。用单位圆上的均匀布点方法估计覆盖面积S的均值、方差及其分布函数,结果显示Beta分布可以较好的拟合S/π的分布。为了增大覆盖面积,推荐采用序贯方法安排随机圆,模拟结果显示序贯方法非常有效。本文还指出了序贯方法在加权单位圆的覆盖问题中效果也显著。 相似文献
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几何分布的一类贝叶斯停止判决法则 总被引:7,自引:0,他引:7
1 引言 以节约样本为目的序贯方法在数理统计中占有重要地位.从实际工作的角度出发,人们往往更强调时间的价值,希望当有足够的证据做出推断时应尽早停止试验,这样就提出了时间序贯计划.近年来,时间序贯方法得到了迅速发展(见[1—6]).[3]和[6]讨论了指数分布的时间序贯检验问题. [5]讨论了单试验平台情形,几何分布的时间序贯检验问题,适合于受试样品比较昂贵的情形.本文讨论多试验平台,受试品比较廉价而试验时间(次数)比较宝贵情形的几何分布的检验问题. 相似文献
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序集抽样是一种适用于准确测量花费太高而排序费用可以忽略不记时的一种抽样方法.讨论了序集抽样下的对于一般分布族M估计的相合性和渐近正态性并且通过随机加权的方法来估计M估计的分布. 相似文献
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通常高成本、破坏性的抽样检验需采用具有最大样本量限制的序贯检验方法.立足于设计出最大样本量尽量小的序贯检验方案,本文基于Koopman-Darmois分布族建立了序贯网图检验方法.与目前广泛采用的截尾序贯概率比检验方法相比,序贯网图检验方案具有更小的样本量上界,更适合高成本、破坏性的抽样检验. 相似文献
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刘宝光 《高校应用数学学报(A辑)》1990,5(3):388-396
在火炸药工程技术中,常要凭一种特殊形式的统计数据评定火炸药制品的感度。本文概述我们为改善和发展解决这一问题的统计方法近几年来所做的主要工作。分三个方面:(1)对于该领域的主要方法升降法,给出了修正的估值公式,以消除方法的系统误差;(2)提出了逐次调整设计参数的试验设计方法,以及与之配合的多组样本组合分析公式,保证以合理的试验量达到预定估值精度;(3)用平滑原理和数值最优化给出了一种分析感度数据的新方法。 相似文献
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A supersaturated design (SSD), whose run size is not enough for estimating all the main effects, is commonly used in screening experiments. It offers a potential useful tool to investigate a large number of factors with only a few experimental runs. The associated analysis methods have been proposed by many authors to identify active effects in situations where only one response is considered. However, there are often situations where two or more responses are observed simultaneously in one screening experiment, and the analysis of SSDs with multiple responses is thus needed. In this paper, we propose a two-stage variable selection strategy, called the multivariate partial least squares-stepwise regression (MPLS-SR) method, which uses the multivariate partial least squares regression in conjunction with the stepwise regression procedure to select true active effects in SSDs with multiple responses. Simulation studies show that the MPLS-SR method performs pretty good and is easy to understand and implement. 相似文献
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《Optimization》2012,61(12):2269-2295
ABSTRACTIn this paper, we propose a best-response approach to select an equilibrium in a two-player generalized Nash equilibrium problem. In our model we solve, at each of a finite number of time steps, two independent optimization problems. We prove that convergence of our Jacobi-type method, for the number of time steps going to infinity, implies the selection of the same equilibrium as in a recently introduced continuous equilibrium selection theory. Thus the presented approach is a different motivation for the existing equilibrium selection theory, and it can also be seen as a numerical method. We show convergence of our numerical scheme for some special cases of generalized Nash equilibrium problems with linear constraints and linear or quadratic cost functions. 相似文献
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Kangning Wang 《Annals of the Institute of Statistical Mathematics》2018,70(2):323-351
Spatial semiparametric varying coefficient models are a useful extension of spatial linear model. Nevertheless, how to conduct variable selection for it has not been well investigated. In this paper, by basis spline approximation together with a general M-type loss function to treat mean, median, quantile and robust mean regressions in one setting, we propose a novel partially adaptive group \(L_{r} (r\ge 1)\) penalized M-type estimator, which can select variables and estimate coefficients simultaneously. Under mild conditions, the selection consistency and oracle property in estimation are established. The new method has several distinctive features: (1) it achieves robustness against outliers and heavy-tail distributions; (2) it is more flexible to accommodate heterogeneity and allows the set of relevant variables to vary across quantiles; (3) it can keep balance between efficiency and robustness. Simulation studies and real data analysis are included to illustrate our approach. 相似文献
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本文提出了参数设计中方差估计的一种新方法 -非参数估计方法 ,用以代替田口的信噪比中的方差估计。实例表明 ,该方法不但可以对因子进行分类 ,而且可以进行模型拟合的检查 相似文献
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We consider the problem of constructing nonlinear regression models in the case that the structure of data has discontinuities
at some unknown points. We propose two-stage procedure in which the change points are detected by relevance vector machine
at the first stage, and the smooth curve are effectively estimated along with the technique of regularization method at the
second. In order to select tuning parameters in the regularization method, we derive a model selection and evaluation criterion
from information-theoretic viewpoints. Simulation results and real data analyses demonstrate that our methodology performs
well in various situations. 相似文献
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Junguang?Zhang Xiwei?Song Hongyu?Chen Ruixia ?Shi 《The Journal of the Operational Research Society》2016,67(9)
It has been well accepted in the literature that co-dependency between project activity durations is caused by resource tightness and network complexity. However, we show that information flow interaction between activities is the key factor for it. Based on whether there exist spliced relationships between activities, we introduce the concept of rework safety time. We propose a method to compute the rework safety time using the information output and input time factors, rework probability matrix, and rework impact matrix. We achieve the optimization of the critical chain sequencing via the design structure matrix so that the dependency between activities is reduced. The project buffer is then determined by the tail concentration method based on the optimized chain. The empirical results show that, as opposed to the traditional RSEM method, our approach improves the project buffer consumption rate, shortens project duration, reduces project cost, and increases project on-time completion rate. 相似文献
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Model detection and variable selection for varying coefficient models with longitudinal data 下载免费PDF全文
In this paper, we consider the problem of variable selection and model detection in varying coefficient models with longitudinal data. We propose a combined penalization procedure to select the significant variables, detect the true structure of the model and estimate the unknown regression coefficients simultaneously. With appropriate selection of the tuning parameters, we show that the proposed procedure is consistent in both variable selection and the separation of varying and constant coefficients, and the penalized estimators have the oracle property. Finite sample performances of the proposed method are illustrated by some simulation studies and the real data analysis. 相似文献
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We propose a method for selecting variables in latent class analysis, which is the most common model-based clustering method
for discrete data. The method assesses a variable’s usefulness for clustering by comparing two models, given the clustering
variables already selected. In one model the variable contributes information about cluster allocation beyond that contained
in the already selected variables, and in the other model it does not. A headlong search algorithm is used to explore the
model space and select clustering variables. In simulated datasets we found that the method selected the correct clustering
variables, and also led to improvements in classification performance and in accuracy of the choice of the number of classes.
In two real datasets, our method discovered the same group structure with fewer variables. In a dataset from the International
HapMap Project consisting of 639 single nucleotide polymorphisms (SNPs) from 210 members of different groups, our method discovered
the same group structure with a much smaller number of SNPs. 相似文献
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Li-Ping Zhu Lin-Yi Qian Jin-Guan Lin 《Annals of the Institute of Statistical Mathematics》2011,63(6):1277-1293
In this paper we discuss variable selection in a class of single-index models in which we do not assume the error term as
additive. Following the idea of sufficient dimension reduction, we first propose a unified method to recover the direction,
then reformulate it under the least square framework. Differing from many other existing results associated with nonparametric
smoothing methods for density function, the bandwidth selection in our proposed kernel function essentially has no impact
on its root-n consistency or asymptotic normality. To select the important predictors, we suggest using the adaptive lasso method which
is computationally efficient. Under some regularity conditions, the adaptive lasso method enjoys the oracle property in a
general class of single-index models. In addition, the resulting estimation is shown to be asymptotically normal, which enables
us to construct a confidence region for the estimated direction. The asymptotic results are augmented through comprehensive
simulations, and illustrated by an analysis of air pollution data. 相似文献
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The aim of this paper is to propose a variational piecewise constant level set method for solving elliptic shape and topology optimization problems. The original model is approximated by a two-phase optimal shape design problem by the ersatz material approach. Under the piecewise constant level set framework, we first reformulate the two-phase design problem to be a new constrained optimization problem with respect to the piecewise constant level set function. Then we solve it by the projection Lagrangian method. A gradient-type iterative algorithm is presented. Comparisons between our numerical results and those obtained by level set approaches show the effectiveness, accuracy and efficiency of our algorithm. 相似文献