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61.
62.
邹友金 《上海理工大学学报(社会科学版)》1989,(4)
本文在分析一维优化方法的比例因子法的基础上,提出了一种直接调整步长的最优步长因子法并给出框图。该法较比例因子法理论上完善,迭代控制可靠。 相似文献
63.
Regularization and variable selection via the elastic net 总被引:2,自引:0,他引:2
Hui Zou Trevor Hastie 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2005,67(2):301-320
Summary. We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, where strongly correlated predictors tend to be in or out of the model together. The elastic net is particularly useful when the number of predictors ( p ) is much bigger than the number of observations ( n ). By contrast, the lasso is not a very satisfactory variable selection method in the p ≫ n case. An algorithm called LARS-EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lasso. 相似文献
64.
矿井掘进工作面安全评价的灰色聚类方法 总被引:2,自引:0,他引:2
本文用灰色聚类方法[1]讨论了煤矿掘进工作面安全评价问题,提出了一种新的安全评价方法─灰色聚类综合法。同时,本文对灰色聚类的算法作了改进,改进后的算法便于记忆和应用。 相似文献
65.
在网站后台数据库查询程序设计中,本文解决了三个关键问题:(1)在表单内插入一个名称为“Send”的隐藏字段,将表单网页和表单处理程序合并为一个ASP程序,从而避免了用户多次查询时在两个页面之间的频繁切换。(2)在函数调用时,通过变换参数的方法实现了对不同数据库的选择查询。(3)利用数组存储技术和循环控制结构,将多种查询结果组织在同一个页面之内,不仅方便了用户浏览,而且减少了网页维护的负担。 相似文献
66.
Gyula O. H. Katona 《Journal of statistical planning and inference》2002,100(2):319-336
One unknown element of an n-element set is sought by asking if it is contained in given subsets. It is supposed that the question sets are of size at most k and all the questions are decided in advance, the choice of the next question cannot depend on previous answers. At most l of the answers can be incorrect. The minimum number of such questions is determined when the order of magnitude of k is n with <1. The problem can be formulated as determination of the maximum sized l-error-correcting code (of length n) in which the number of ones in a given position is at most k. 相似文献
67.
A smoothing parameter inversely proportional to the square root of the true density is known to produce kernel estimates of the density having faster bias rate of convergence. We show that in the case of kernel-based nonparametric hazard rate estimation, a smoothing parameter inversely proportional to the square root of the true hazard rate leads to a mean square error rate of order n ?8/9, an improvement over the standard second order kernel. An adaptive version of such a procedure is considered and analyzed. 相似文献
68.
Search design is searching and estimating for a few non zero effects in a large set of effects along with estimation of elements in a set of unknown parameters. In presence of noise, the probability of discrimination between the true non zero effect from an alternative one depends on the design and an unknown parameter, say ρ. We develop a new criterion for design comparison which is independent of ρ and for a family density weight function show that it discriminates and ranks the designs precisely. This criterion is invariance to the variable noise which may be present between designs due to noise factors. This allows us to extend the design comparison to classes of equivalent designs. 相似文献
69.
Three parameters—sample size, sampling intervals, and the control limits—must be determined when the x bar chart to monitor a manufacturing process. The constant sampling intervals were widely employed because of its administrative simplicity. However, the variable sampling interval (VSI) has recently been shown to give substantially faster detection of most process shifts than fixed-sampling-interval (FSI) for x-bar charts. In addition, these measurements in the subgroup are assumed to be normally distributed. That assumption may not be tenable. This investigation compares the economic design of x-bar control charts for non normal data under Weibull shock models with various sampling avenues. 相似文献
70.
This article considers the adaptive lasso procedure for the accelerated failure time model with multiple covariates based on weighted least squares method, which uses Kaplan-Meier weights to account for censoring. The adaptive lasso method can complete the variable selection and model estimation simultaneously. Under some mild conditions, the estimator is shown to have sparse and oracle properties. We use Bayesian Information Criterion (BIC) for tuning parameter selection, and a bootstrap variance approach for standard error. Simulation studies and two real data examples are carried out to investigate the performance of the proposed method. 相似文献