A simple,doubly robust,efficient estimator for survival functions using pseudo observations

Survival functions are often estimated by nonparametric estimators such as the Kaplan‐Meier estimator. For valid estimation, proper adjustment for confounding factors is needed when treatment assignment may depend on confounding factors. Inverse probability weighting is a commonly used approach, especially when there is a large number of potential confounders to adjust for. Direct adjustment may also be used if the relationship between the time‐to‐event and all confounders can be modeled. However, either approach requires a correctly specified model for the relationship between confounders and treatment allocation or between confounders and the time‐to‐event. We propose a pseudo‐observation–based doubly robust estimator, which is valid when either the treatment allocation model or the time‐to‐event model is correctly specified and is generally more efficient than the inverse probability weighting approach. The approach can be easily implemented using standard software. A simulation study was conducted to evaluate this approach under a number of scenarios, and the results are presented and discussed. The results confirm robustness and efficiency of the proposed approach. A real data example is also provided for illustration.     

Generalized neighbor designs with block size 3

A generalized neighbor design relaxes the equality condition on the number of times two treatments as neighbors in the design. In this article, we have considered the construction of some classes of generalized neighbor designs with block size k=3 by using the method of cyclic shifts. The distinguishing feature of this construction method is that the properties of a design can easily be obtained from the sets of shifts instead of constructing the actual blocks of the design. A catalog of generalized neighbor designs with block size k=3 is compiled for v∈{5,6,…,18} treatments and for different replications. We provide the reader with a simpler method of construction, and in general the catalog that gives an open choice to the experimenter for selecting any class of neighbor designs.     

用数值模拟方法研究气井产量递减

运用数值模拟软件的单井模拟器,建立了异常高压气藏气井和正常压力气藏气井产量递减的单井模型,得到了异常高压气藏气井和正常压力气藏气井的产量递减数据。根据这些产量递减数据,由两种产量递减自动拟合模型分别计算了异常高压气藏气井和正常压力气藏气井的产量递减参数、地层物性参数(k_gh、k_g/Φ)及地质储量。为了提高计算精度,采用根据拟稳态的产量递减数据(去掉不稳定的递减数据)来反求地层参数和地质储量,并根据自动拟合模型的检验标准对计算结果进行了检验。结果表明,由两种产量递减自动拟合模型计算的产量递减参数和地质储量与数值模拟的计算结果非常吻合,再次证明了这两种产量递减模型的适用性。     

P2P应用层数据流量优化

为减少对主干网络带宽的消耗,提出了一套数据流量优化方法。首先通过把Peer间的邻居关系明确划分为物理邻居关系和逻辑邻居关系,并用探路者算法来发现Peer的物理邻居,实现拓扑匹配;然后在数据调度算法中,引入通报/退避机制,把大部分数据传输控制在城域网络内部。通过建立模拟仿真环境进行实验分析,证实了该方法可以减少90%以上的网络数据流量。     

基于求解TSP问题的双向扩展差额算法

旅行商(TSP)问题是典型的组合优化中的NP-hard难题.本文在最近城市搜索法和两端延伸最近城市搜索法基础上提出了双向扩展差额求解算法,并分析了算法的复杂度.采用以上三种算法求解了TSPLIB标准库中多个算例,比较结果表明本算法能够更快的找到更优的方案,具有更好的综合性能.     

Generalized Maximum Spacing Estimation for Multivariate Observations

In this paper, the maximum spacing method is considered for multivariate observations. Nearest neighbour balls are used as a multidimensional analogue to univariate spacings. A class of information‐type measures is used to generalize the concept of maximum spacing estimators. Weak and strong consistency of these generalized maximum spacing estimators are proved both when the assigned model class is correct and when the true density is not a member of the model class. An example of the generalized maximum spacing method in model validation context is discussed.     

Root-n-consistent semiparametric estimation of partially linear models based on k-nn method

In the context of the partially linear semiparametric model examined by Robinson (1988), we show that root-n-consisten estimation results established using kernel and series methods can also be obtained by using k-nearest-neighbor (k-nn) method.     

双光子对撞过程的人工色理论尝试

考虑了多标度人工色 (multiscalewalkingtechnicolor,简称MWTC)模型中赝标哥尔斯通玻色子 (pseudo Goldstonebosons ,简称PGBs)对γγ→bb过程的Yukawa修正。发现在一定的参数范围内 ,PGBs对γγ→bb散射截面的修正超过 10 % ;而PGBs对过程e+ e-→γγ→bb的相对修正 ,在laserback scatteringphotons模式下最大可达 - 5 9% ,在beamstrahlungphotons模式下最大只有 - 2 2 % ;这些修正将为在下一代高能光子碰撞实验上寻找人工色理论的信息提供参考     

Bayesian Inference and Forecasting in Dynamic Neural Networks with Fully Markov Switching ARCH Noises

We deal with one-layer feed-forward neural network for the Bayesian analysis of nonlinear time series. Noises are modeled nonlinearly and nonnormally, by means of ARCH models whose parameters are all dependent on a hidden Markov chain. Parameter estimation is performed by sampling from the posterior distribution via Evolutionary Monte Carlo algorithm, in which two new crossover operators have been introduced. Unknown parameters of the model also include the missing values which can occur within the observed series, so, considering future values as missing, it is also possible to compute point and interval multi-step-ahead predictions.     

Nonparametric multiple comparison procedures for unbalanced one-way factorial designs

In this paper, we present several nonparametric multiple comparison (MC) procedures for unbalanced one-way factorial designs. The nonparametric hypotheses are formulated by using normalized distribution functions and the comparisons are carried out on the basis of the relative treatment effects. The proposed test statistics take the form of linear pseudo rank statistics and the asymptotic joint distribution of the pseudo rank statistics for testing treatments versus control satisfies the multivariate totally positive of order two condition irrespective of the correlations among the rank statistics. Therefore, in the context of MCs of treatments versus control, the nonparametric Simes test is validated for the global testing of the intersection hypothesis. For simultaneous testing of individual hypotheses, the nonparametric Hochberg stepup procedure strongly controls the familywise type I error rate asymptotically. With regard to all pairwise comparisons, we generalize various single-step and stagewise procedures to perform comparisons on the relative treatment effects. To further compare with normal theory counterparts, the asymptotic relative efficiencies of the nonparametric MC procedures with respect to the parametric MC procedures are derived under a sequence of Pitman alternatives in a nonparametric location shift model for unbalanced one-way layouts. Monte Carlo simulations are conducted to demonstrate the validity and power of the proposed nonparametric MC procedures.