基于Bootstrap方法的密封寿命可靠性评估

针对高可靠、长寿命密封件在小样本试验下的可靠性寿命评估需求,提出一种基于虚拟增广样本和Bootstrap方法的密封寿命小样本数据可靠性评估方法。并以轴用阶梯圈为例,进行寿命可靠性评估。首先通过虚拟增广法将轴用阶梯圈台架寿命试验数据样本数增广至10个,使得样本数满足Bootstrap方法的适用条件;然后再利用Bootstrap方法得到轴用阶梯圈的寿命可靠性评估结果。     

Nonlinear Factor-Augmented Predictive Regression Models with Functional Coefficients

This article introduces a new class of functional-coefficient predictive regression models, where the regressors consist of auto-regressors and latent factor regressors, and the coefficients vary with certain index variable. The unobservable factor regressors are estimated through imposing an approximate factor model on high dimensional exogenous variables and subsequently implementing the classical principal component analysis. With the estimated factor regressors, a local linear smoothing method is used to estimate the coefficient functions (with appropriate rotation) and obtain a one-step ahead nonlinear forecast of the response variable, and then a wild bootstrap procedure is introduced to construct the prediction interval. Under regularity conditions, the asymptotic properties of the proposed methods are derived, showing that the local linear estimator and the nonlinear forecast using the estimated factor regressors are asymptotically equivalent to those using the true latent factor regressors. The developed model and methodology are further generalized to the factor-augmented vector predictive regression with functional coefficients. Finally, some extensive simulation studies and an empirical application to forecast the UK inflation are given to examine the finite-sample performance of the proposed model and methodology.     

A new MM algorithm for constrained estimation in the proportional hazards model

The constrained estimation in Cox’s model for the right-censored survival data is studied and the asymptotic properties of the constrained estimators are derived by using the Lagrangian method based on Karush–Kuhn–Tucker conditions. A novel minorization–maximization (MM) algorithm is developed for calculating the maximum likelihood estimates of the regression coefficients subject to box or linear inequality restrictions in the proportional hazards model. The first M-step of the proposed MM algorithm is to construct a surrogate function with a diagonal Hessian matrix, which can be reached by utilizing the convexity of the exponential function and the negative logarithm function. The second M-step is to maximize the surrogate function with a diagonal Hessian matrix subject to box constraints, which is equivalent to separately maximizing several one-dimensional concave functions with a lower bound and an upper bound constraint, resulting in an explicit solution via a median function. The ascent property of the proposed MM algorithm under constraints is theoretically justified. Standard error estimation is also presented via a non-parametric bootstrap approach. Simulation studies are performed to compare the estimations with and without constraints. Two real data sets are used to illustrate the proposed methods.     

Wind of change: Small-scale electricity production and distribution-grid efficiency in Sweden

In this paper, we measure the technical efficiency for local electricity distribution firms in Sweden, and in particular how small and micro-scale generation affects efficiency scores. Using a two-stage data envelopment analysis to model the technical efficiency and a double bootstrap approach to estimate the determinants of inefficiencies, we show that firms are heterogeneous in terms of inefficiency, but that a large share of small and micro-scale generation is not associated with more inefficient operations.     

基于开关电容的三端口DC-DC变换器

三端口直流变换器(TPC)应用于新能源供电系统与电动汽车供电系统,可将系统中原有的多个单向和双向直流变换器在电路结构上实现合并,具有结构简单、成本低、控制灵活等优点。根据TPC的分类和组成规则构建一族含有开关电容、自举电路、BUCK、BOOST电路的高压比三端口直流变换器。形成的新型三端口变换器具有压比高、结构灵活、调压范围广等特点,可以很好地应用在新能源发电应用系统中。最后对提出的新拓扑进行理论分析和实验验证。     

原竹材料抗弯性能试验研究

开展了原竹材料抗弯性能试验,探究了竹材抗弯强度和弹性模量与高度、壁厚、周长的关系,采用Bootstrap法分析了竹材抗弯强度标准值,基于可靠度理论研究了原竹材料的抗弯强度设计值。结果表明:竹片抗弯加载经历较长的弹性阶段,塑性阶段较短,竹材抗弯承载力随高度增加而减小; 竹片抗弯强度和弹性模量随高度增加而增大,随壁厚和周长增大而减小,竹片抗弯强度、弹性模量与高度、壁厚和周长具有较好的拟合优度,拟合公式可对竹材力学性能进行预测; 样本数量对竹材抗弯强度的抽样误差具有显著影响,通过Bootstrap重抽样法分析标准值能够有效减小误差,采用该法进行10 000次重抽样分析得到的原竹材料强度标准值为126.75 MPa; 可靠度指标β随抗力分项系数γ_R和荷载比ρ的增大而增大; 荷载比ρ>0时,目标可靠度下的抗力分项系数γ_R在恒载+雪荷载情况下最大,在恒载+办公楼面活荷载情况下最小,计算得到的3个安全等级下的原竹材料抗弯强度设计值分别为27.670,29.884,32.084 MPa。     

Structural and operational management of Turkish airports: a bootstrap data envelopment analysis of efficiency

This paper explores the structural and operational dimensions of the efficiencies of airports. The two-stage procedure is suggested to assess the efficiencies of airports in this study. In the first-stage, Classification and Regression Tree, which is one of the machine-learning approaches used to divide the airports into homogeneous and thus comparable sub-groups. In the second stage, the bootstrap data envelopment analysis approach obtains more precise structural and operational efficiency scores. To illustrate the proposed framework use, we applied it to a real case associated with Turkish airports. The results demonstrate that this framework presents a more comprehensive assessment of airport performance rather than conventional data envelopment analysis models. Moreover, it provides to show the deficiencies of the structural and operational management of airports. The findings can help anywhere airport authorities as well as Turkish airport authorities.     

Modelling commuting time in the US: Bootstrapping techniques to avoid overfitting

The research on commuting has emerged in recent decades, but the issue of whether the empirical techniques used are appropriate has not been analysed. Thus, results from prior research could be based on non-accurate models, leading to misleading conclusions. We apply an algorithmic approach based on bootstrapping, variable selection, and mean absolute prediction errors, which is designed to avoid overfitting. Using the American Time Use Survey, we find that models with a reduced set of explanatory variables have similar accuracy to standard econometric models. Our results shed light on the importance of determining whether models can be overfitted.     

Estimating probabilistic fatigue of Nitinol with scarce samples

Current work estimates probabilistic fatigue life efficiently with scarce samples. The underlying idea of the estimation is to approximate the cumulative distribution function of the fatigue life in a transformed space using a third order polynomial subject to monotonicity constraint. The variations associated with the estimated quantiles are quantified using bootstrap. The proposed approach is validated on a data obtained from literature. It is observed that the life quantiles with reasonable accuracy can be estimated even with 10 samples. Finally, the probabilistic fatigue of Nitinol in austenitic condition is obtained with limited experiments.     

Bootstrap方法在Jensen Alpha估计中的运用

詹森差别表现指数(Jensen Alpha)是使用较多的一种评价投资组合业绩的指标。进一步分析Bootstrap方法的基本原理,探讨将Bootstrap运用于Jensen Alpha估计的具体过程,从而解决了运用普通最小二乘法(OLS)估计Jensen Alpha存在的缺陷,提高了Jensen Alpha估计的稳健性,对于投资组合业绩的评价具有一定的参考意义。