On the Power Performance of Test Statistics for the Generalized Rayleigh Interval Grouped Data

In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.

Bootstrap Confidence Intervals for Proportions of Unequal Sized Groups Adjusted for Overdispersion

Group testing is a method of pooling a number of units together and performing a single test on the resulting group. It is an appealing option when few individual units are thought to be infected leading to reduced costs of testing as compared to individually testing the units. Group testing aims to identify the positive groups in all the groups tested or to estimate the proportion of positives (p) in a population. Interval estimation methods of the proportions in group testing for unequal group sizes adjusted for overdispersion have been examined. Lately improvement in statistical methods allows the construction of highly accurate confidence intervals (CIs). The aim here is to apply group testing for estimation and generate highly accurate Bootstrap confidence intervals (CIs) for the proportion of defective or positive units in particular. This study provided a comparison of several proven methods of constructing CIs for a binomial proportion after adjusting for overdispersion in group testing with groups of unequal sizes. Bootstrap resampling was applied on data simulated from binomial distribution, and confidence intervals with high coverage probabilities were produced. This data was assumed to be overdispersed and independent between groups but correlated within these groups. Interval estimation methods based on the Wald, the Logit and Complementary log-log (CLL) functions were considered. The criterion used in the comparisons is mainly the coverage probabilities attained by nominal 95% CIs, though interval width is also regarded. Bootstrapping produced CIs with high coverage probabilities for each of the three interval methods.

Colorectal and interval cancers of the Colorectal Cancer Screening Program in the Basque Country (Spain)

AIM To assess proportions, related conditions and survival of interval cancer(IC).METHODS The programme has a linkage with different clinical databases and cancer registers to allow suitable evaluation. This evaluation involves the detection of ICs after a negative faecal inmunochemical test(FIT), interval cancer FIT(IC-FIT) prior to a subsequent invitation, and the detection of ICs after a positive FIT and confirmatory diagnosis without colorectal cancer(CRC) detected and before the following recommended c o l o n o s c o p y, I C-c o l o n o s c o p y. W e c o n d u c t e d a retrospective observational study analyzing from January 2009 to December 2015 1193602 invited people onto the Programme(participation rate of 68.6%).RESULTS Two thousand five hundred and eighteen cancers were diagnosed through the programme, 18 cases of IC-colonoscopy were found before the recommended follow-up(43542 colonoscopies performed) and 186 IC-FIT were identified before the following invitation of the 769200 negative FITs. There was no statistically significant relation between the predictor variables of ICs with sex, age and deprivation index, but there was relation between location and stage. Additionally, it was observed that there was less risk when the location was distal rather than proximal(OR = 0.28, 95%CI: 0.20-0.40, P < 0.0001), with no statistical significance when the location was in the rectum as opposed to proximal. When comparing the screen-detected cancers(SCs) with ICs, significant differences in survival were found(P < 0.001); being the 5-years survival for SCs 91.6% and IC-FIT 77.8%.CONCLUSION These findings in a Population Based CRC Screening Programme indicate the need of population-based studies that continue analyzing related factors to improve their detection and reducing harm.

Honesty, power and bootstrapping in composite interval quantitative trait locus mapping

In a typical composite interval mapping experiment, the probability of obtaining false QTL is likely to be at least an order of magnitude greater than the nominal experiment-wise Type I error rate, as set by permutation test. F2 mapping crosses were simulated with three different genetic maps. Each map contained ten QTL on either three, six or twelve linkage groups. QTL effects were additive only, and heritability was 50%. Each linkage group had 11 evenly-spaced (10 cM) markers. Selective genotyping was used. Simulated data were analyzed by composite interval mapping with the Zmapqtl program of QTL Cartographer. False positives were minimized by using the largest feasible number of markers to control genetic background effects. Bootstrapping was then used to recover mapping power lost to the large number of conditioning markers. Bootstrapping is shown to be a useful tool for QTL discovery, although it can also produce false positives. Quantitative bootstrap support—the proportion of bootstrap replicates in which a significant likelihood maximum occurred in a given marker interval—was positively correlated with the probability that the likelihood maxima revealed a true QTL. X-linked QTL were detected with much lower power than autosomal QTL. It is suggested that QTL mapping experiments should be supported by accompanying simulations that replicate the marker map, crossing design, sample size, and method of analysis used for the actual experiment.

A Tight Prediction Interval for False Discovery Proportion under Dependence

The false discovery proportion (FDP) is a useful measure of abundance of false positives when a large number of hypotheses are being tested simultaneously. Methods for controlling the expected value of the FDP, namely the false discovery rate (FDR), have become widely used. It is highly desired to have an accurate prediction interval for the FDP in such applications. Some degree of dependence among test statistics exists in almost all applications involving multiple testing. Methods for constructing tight prediction intervals for the FDP that take account of dependence among test statistics are of great practical importance. This paper derives a formula for the variance of the FDP and uses it to obtain an upper prediction interval for the FDP, under some semi-parametric assumptions on dependence among test statistics. Simulation studies indicate that the proposed formula-based prediction interval has good coverage probability under commonly assumed weak dependence. The prediction interval is generally more accurate than those obtained from existing methods. In addition, a permutation-based upper prediction interval for the FDP is provided, which can be useful when dependence is strong and the number of tests is not too large. The proposed prediction intervals are illustrated using a prostate cancer dataset.

Variation regularity of metal magnetic memory signals with inspecting time-interval and location

Influences of inspecting time-interval and location on varying behavior of metal magnetic memory (MMM) signals of defects were studied. Different areas in two precracked weldments were inspected at different time-intervals by type TSC-1M-4 stress-concentration magnetic inspector to obtain MMM signals. Mechanisms of MMM signals varying behavior with inspecting time and space were analyzed and discussed respectively. It is found that MMM signals don't change with inspecting time-interval, since stress field and magnetic leakage field maintain unchanged at any time after welding. On the other hand, MMM signals differ greatly for different inspecting locations, because stress field and magnetic leakage field are unevenly distributed in defective ferromagnetic materials.

拉萨地区儿童临床常用生化检验项目参考区间验证

目的验证卫生行业标准WS/T780-2021《儿童临床常用生化检验项目参考区间》,判断其是否适用于我实验室所服务的拉萨地区儿童。方法在拉萨市人民医院体检人群中筛选健康体检儿童,按照参考区间建立时的性别、年龄亚组划分标准,每亚组筛选合格参考个体不少于20名,按WS/T661《静脉血液标本采集指南》采集样本,在迈瑞BS2000全自动生化分析仪上进行生化项目检测,将检测结果与行标参考区间进行比较,并对各检测参数进行年龄性别间差异比较。结果17~18岁女孩碱性磷酸酶(ALP)符合率为73.6%,未通过验证;其余的各亚组符合率均>90%,通过验证。对各项目年龄组间差异分析,除血清氯(Cl)在年龄组间差异无统计学意义,其余各项目在年龄组间差异均有统计学意义(P<0.05)。对相同年龄段性别间差异分析,天门冬氨酸氨基转移酶(AST)13~18岁男女组间差异无统计学意义,无机磷(IP)15~18岁男女组间差异无统计学意义,其余各项目在相同年龄段性别间差异均有统计学意义(P<0.05)。结论《儿童临床常用生化检验项目参考区间》基本适用于拉萨地区儿童,17~18岁女孩碱性磷酸酶参考区间应单独制定;儿童生化检验项目在不同年龄及性别间有较大差异,实验室在引用或建立儿童生化项目参考区间时应重视年龄及性别划分。

基于分布假设检验的风电机组静态偏航误差诊断方法研究

通过确定敏感风速区间并检测功率分布,实现对风电机组静态偏航误差值的估计。利用风电机组的实际运行数据对所提方法的有效性进行验证,并与基于功率曲线的诊断方法进行对比。结果表明,所提方法能够准确量化不同偏航误差区间的数据分布差异,精准识别出静态偏航误差所在的偏航角区间,诊断的准确性较高。

制导武器命中精度估计方法与检验方法一致性研究

针对制导武器命中精度估计方法和检验方法存在的联系以及原理性差异,对两种命中精度评定方法的一致性进行了研究。从双方风险角度研究了小子样条件对命中精度点估计和区间估计方法的影响,明确了提升命中精度评定准确性的手段;在分析命中精度指标与检验方法关系基础上,通过将双方风险与区间上界估计方法进行比较,明确了命中精度指标为备择假设的检验方法;从双方风险层面进一步分析了区间估计方法与检验方法的一致性。结果表明:对于区间估计方法和检验方法,通过合理调整置信水平参数和检出比参数,能够实现两种方法双方风险的一致性,但两种评定方法理论基础不同,进行精度评定会存在评定结论不一致的现象,该现象出现概率与制导武器自身精度有关。

高速铁路联调联试工务数据管理与应用

以提升高速铁路联调联试工务专业试验数据归集、处理、分析自动化和智能化水平为目的,开展联调联试工务数据管理与应用技术研究,制定联调联试数据接口规范,研究提出试验数据综合分析应用系统功能设计、技术架构与部署方案。系统接入轨道、道岔、桥梁、隧道、路基等工务专业联调联试数据,实现数据集中管理和信息共享,提升了试验数据管理水平。基于历年试验数据,开展数据挖掘与智能分析,提供试验数据异常值判识、多维综合分析、试验报告自动生成等功能。

半成岩结构面原位直剪试验及抗剪参数的研究

半成岩作为一种特殊性岩土,工程性质受岩体结构面的影响较大,因此,确定结构面的剪切强度参数十分重要。文中根据半成岩原位剪切试验结果,采用概率统计分析方法,对抗剪强度参数进行估算,同时对M-C准则模型、B-B准则模型的95%预测区间和95%置信区间进行拟合及评价。结果表明,B-B准则模型的95%置信区间较M-C准则的范围更窄,参数估计的可靠性更高,尤其低法向应力水平下,B-B准则模型明显优于M-C准则模型,其抗剪强度参数更准确。

动态心电图QTc间期联合运动平板试验对冠心病心肌缺血的诊断价值分析

目的:探讨动态心电图QTc间期联合运动平板试验诊断冠心病心肌缺血的价值。方法:选取昆山市第一人民医院2019年1月—2022年12月收治的108例疑似冠心病心肌缺血患者,均行运动平板试验、动态心电图检查。以冠脉造影诊断结果为金标准,对比以上两种方法诊断冠心病心肌缺血的效能。结果:108例疑似冠心病心肌缺血患者经冠脉造影检查,阴性30例,占27.78%,阳性78例,占72.22%。动态心电图QTc间期诊断为阴性共有20例,阳性51例,运动平板试验诊断为阴性共有25例,阳性50例,动态心电图QTc间期联合运动平板试验,诊断为阴性共有29例,阳性62例。动态心电图QTc间期联合运动平板试验诊断冠心病心肌缺血的敏感度为79.49%,特异度为96.67%,准确度为84.26%,联合诊断的敏感度、准确度均高于动态心电图QTc间期、运动平板试验单一诊断,联合诊断的特异度高于动态心电图QTc间期单一诊断,差异均有统计学意义(P<0.05)。结论:与单一诊断相比,动态心电图QTc间期联合运动平板试验诊断冠心病心肌缺血的价值更高,可为临床诊断提供可靠的心电学依据。

基于bayes成功型试验模型的整车试验可靠度分析

为解决整车道路及耐久试验存在的试验成本高、样本量不统一、试验周期长、实验数据不够精确等实际问题,依据bayes成功型试验公式及Lipson变换公式,从置信度和可靠度方面分析试验样本量与可靠度、强化系数之间的关系,给出制定最优样本量、强度系数的理论方法.提出在某个置信区间内的可靠度及样本量的确定方案,实现了在设定置信区间及可靠度范围内的样本量最优解.对试验场耐久测试亦或公共道路试验的可靠性指标度量及样本量确定具有实际指导意义.

参数估计与假设检验理实一体化教学探索

文章在阐明标准正态分布分位数、置信水平、置信区间和样本均值的抽样分布的基础上,通过计算样本均值落在总体均值两侧任何位数抽样标准差范围内的概率,运用中心极限定理建立总体均值的参数估计区间;根据估计区间,提出假设检验的基本思想,明确双侧检验和单侧检验的拒绝域,并提醒学生左侧检验与右侧检验容易误判的地方;通过引例,实施理实一体化教学,边讲原理边做实验,化抽象为具体,从具体再到抽象,消除学生对参数估计和假设检验的畏惧感,明晰推导思路,让学生在完成操作任务的过程中学习统计学知识。

波长快速扫描系统的关键技术研究

波长快速扫描系统在算力网络、5G前传网络以及新一代可重构光分插复用系统等领域起着重要作用,整个波长扫描测试系统的性能基本取决于激光器性能的优劣。为此,基于In Ga As P/In P增益芯片优异的宽光谱光学特性和Littman-Metcalf外腔反馈原理研制了一台具备宽调谐范围、高扫描速度以及无模式跳变等特点的可调谐激光器。实验上获得了240 nm/s的最高扫描速度、0.001 nm的最小步进触发间隔、优于±1.3 pm/1 min的波长稳定性、优于2.39 pm的绝对波长精度、优于±0.02 d B/1 min的功率稳定性及无跳模范围为110 nm的单纵模扫频输出。该研究有助于推动波长快速扫描测试系统的研究进程,提升波分复用等器件的测试精度和效率。

合理设计安全仪表功能回路的冗余架构

安全仪表功能(SIF)回路的冗余架构应满足安全和误停车率的要求。结合安全完整性等级(SIL)验证工作的经验,对影响SIF冗余架构设计的标准及各种规定的强制约束和影响SIF回路冗余架构设计的因素,如:安全失效因子、平均失效率及误停车率、共因失效及检验测试时间间隔、仪表测量及制造原理、仪表故障模式对架构降级的约束等,进行了工程分析,给出了合理的冗余架构设计原则。合理的冗余架构设计,应当兼顾SIF回路中的各个部件,并非冗余仪表越多越好,也并非越少越好,在经济条件允许的前提下,合理性是在满足安全及减少误停车率之间平衡的结果。

Planning failure-censored constant-stress partially accelerated life test

This article deals with the case of the failure-censored constant-stress partially accelerated life test （CSPALT） for highly reliable materials or products assuming the Pareto distribution of the second kind. The maximum likelihood （ML） method is used to estimate the parameters of the CSPALT model. The performance of ML estimators is investigated via their mean square error. Also, the average confidence interval length （IL） and the associated co- verage probability （CP） are obtained. Moreover, optimum CSPALT plans that determine the optimal proportion of the test units al- located to each stress are developed. Such optimum test plans minimize the generalized asymptotic variance （GAV） of the ML estimators of the model parameters. For illustration, Monte Carlo simulation studies are given and a real life example is provided.

Bayesian Analysis in Partially Accelerated Life Tests for Weighted Lomax Distribution

Accelerated life testing has been widely used in product life testing experiments because it can quickly provide information on the lifetime distributions by testing products or materials at higher than basic conditional levels of stress,such as pressure,temperature,vibration,voltage,or load to induce early failures.In this paper,a step stress partially accelerated life test(SSPALT)is regarded under the progressive type-II censored data with random removals.The removals from the test are considered to have the binomial distribution.The life times of the testing items are assumed to follow lengthbiased weighted Lomax distribution.The maximum likelihood method is used for estimating the model parameters of length-biased weighted Lomax.The asymptotic confidence interval estimates of the model parameters are evaluated using the Fisher information matrix.The Bayesian estimators cannot be obtained in the explicit form,so the Markov chain Monte Carlo method is employed to address this problem,which ensures both obtaining the Bayesian estimates as well as constructing the credible interval of the involved parameters.The precision of the Bayesian estimates and the maximum likelihood estimates are compared by simulations.In addition,to compare the performance of the considered confidence intervals for different parameter values and sample sizes.The Bootstrap confidence intervals give more accurate results than the approximate confidence intervals since the lengths of the former are less than the lengths of latter,for different sample sizes,observed failures,and censoring schemes,in most cases.Also,the percentile Bootstrap confidence intervals give more accurate results than Bootstrap-t since the lengths of the former are less than the lengths of latter for different sample sizes,observed failures,and censoring schemes,in most cases.Further performance comparison is conducted by the experiments with real data.

Inference for constant-stress accelerated life test with Type-I progressively hybrid censored data from Burr-XII distribution

This paper proposes a simple constant-stress accel- erated life test （ALT） model from Burr type XII distribution when the data are Type-I progressively hybrid censored. The maximum likelihood estimation （MLE） of the parameters is obtained through the numerical method for solving the likelihood equations. Approxi- mate confidence interval （CI）, based on normal approximation to the asymptotic distribution of MLE and percentile bootstrap Cl is derived. Finally, a numerical example is introduced and then a Monte Carlo simulation study is carried out to illustrate the pro- posed method.

Depth Estimates of Buried Utility Systems Using the GPR Method: Studies at the IAG/USP Geophysics Test Site

Identifying underground utilities and predicting their depth are fundamental when it comes to civil engineering excavations, for example, to install or repair water, sewer, gas, electric systems and others. The accidental rupture of these systems can lead to unplanned repair costs, delays in completing the service, and risk injury or death of workers. One way to detect underground utilities is using the GPR-Ground Penetrating Radar geophysical method. To estimate depth, the travel time (two-way travel time) information provided by a radargram is used in conjunction with ground wave velocity, which depends on the dielectric constant of materials, where it is usually assumed to be constant for the area under investigation. This procedure provides satisfactory results in most cases. However, wrong depth estimates can result in damage to public utilities, rupturing pipes, cutting lines and so on. These cases occur mainly in areas that have a marked variation of water content and/or soil lithology, thus greater care is required to determine the depth of the targets. The present work demonstrates how the interval velocity of Dix (1955) can be applied in radargram to estimate the depth of underground utilities compared to the conventional technique of constant velocity applied to the same data set. To accomplish this, synthetic and real GPR data were used to verify the applicability of the interval velocity technique and to determine the accuracy of the depth estimates obtained. The studies were carried out at the IAG/USP test site, a controlled environment, where metallic drums are buried in known positions and depths allowing the comparison of real to estimated depths. Numerical studies were also carried out aiming to simulate the real environment with variation of dielectric constant in depth and to validate the results with real data. The results showed that the depths of the targets were estimated more accurately by means of the interval velocity technique in contrast to the constant velocity technique, minimizing the risks of accidents during excavation.