A new alternative quantile regression model for the bounded response with educational measurements applications of OECD countries

This article introduces a new distribution with two tuning parameters specified on the unit interval. It follows from a ‘hyperbolic secant transformation’ of a random variable following the Weibull distribution. The lack of research on the prospect of hyperbolic transformations providing flexible distributions over the unit interval is a motivation for the study. The main distributional structural properties of the new distribution are established. The different estimation methods and two simulation works have been derived for model parameters. Subsequently, we develop a related quantile regression model for further statistical perspectives. We consider two real data applications based on the educational measurements of both OECD and some non-members of OECD countries. Our regression model aims to relate the desire to get top grades on certain young students in the OECD countries with some of their Education and School Life Index such as reading performance, work environment at home, and paid work experience. It is shown that the elaborated quantile regression model has a better fitting power than famous regression models when the unit response variable possesses skewed distribution as well as two independent variables are significant in the statistical sense at any standard significance level for the median response.     

基于切削温度分析的刀具磨损状态研究

为了解刀具在切削时的实际状况,课题组提出了基于切削温度的刀具状态实时监测的方案。[JP2]采用仿真与试验相结合相验证的方法,对刀具在新刀、早期磨损、严重磨损以及失效4种状态下的切削温度进行分析。通过试验采集刀具磨损及失效的温度信号数据,建立了基于最小模糊度的隶属度函数优化模型,用于诊断刀具加工过程中的磨损及失效状态。应用结果表明,该方法可以实现对刀具磨损及失效状态的实时监测,对提高机床的加工效率及加工精度具有重要意义。     

改性沥青在盐冻融循环条件下的性能研究

通过室内冻融循环试验,对SBS改性沥青和胶粉改性沥青在盐冻融循环前后的三大指标(针入度、软化点、延度)进行了测试。结果表明:两种沥青经盐冻融循环后,温度敏感性增加,高温性能及低温性能均有不同程度降低,且冰冻温度、融雪剂浓度、冻融循环次数对这两种沥青性能影响的程度不同,并通过对两种沥青材料盐冻融循环前后的各项指标对比,发现胶粉改性沥青抗盐冻循环性能优于SBS改性沥青。     

Application of Quasi-Least Squares to Analyse Replicated Autoregressive Time Series Regression Models

Time series regression models have been widely studied in the literature by several authors. However, statistical analysis of replicated time series regression models has received little attention. In this paper, we study the application of the quasi-least squares method to estimate the parameters in a replicated time series model with errors that follow an autoregressive process of order p. We also discuss two other established methods for estimating the parameters: maximum likelihood assuming normality and the Yule-Walker method. When the number of repeated measurements is bounded and the number of replications n goes to infinity, the regression and the autocorrelation parameters are consistent and asymptotically normal for all three methods of estimation. Basically, the three methods estimate the regression parameter efficiently and differ in how they estimate the autocorrelation. When p=2, for normal data we use simulations to show that the quasi-least squares estimate of the autocorrelation is undoubtedly better than the Yule-Walker estimate. And the former estimate is as good as the maximum likelihood estimate almost over the entire parameter space.     

Classification with multiple independent measurements under a separate sampling scheme

In this article, we consider the problem of classifying m independent repeated (multiple) observations coming from the same population under a separate sampling scheme. We derive the asymptotic risk of the proposed NN type classification rule and obtain the upper and lower bounds for it in specific cases in terms of Bayes risk. Using a Monte Carlo simulation study we show that, as m increases, the classification risk decreases.     

Aligned rank statistics for repeated measurement models with orthonormal design, employing a Chernoff–Savage approach

In this paper, aligned rank statistics are considered for testing hypotheses regarding the location in repeated measurement designs, where the design matrix for each set of measurements is orthonormal. Such a design may, for instance, be used when testing for linearity. It turns out that the centered design matrix is not of full rank, and therefore it does not quite satisfy the usual conditions in the literature. The number of degrees of freedom of the limiting chi-square distribution of the test statistic under the null hypothesis, however, is not affected, unless rather special hypotheses are tested. An independent derivation of this limiting distribution is given, using the Chernoff–Savage approach. In passing, it is observed that independence of the choice of aligner, which in the location problem is well-known to be due to cancellation, may in scale problems occur as a result of the type of score function suitable for scale tests. A possible extension to multivariate data is briefly indicated.     

现代会计计量基础的选择

现代会计计量基础的选择使用,是决定会计提供的信息是否可靠、有用的关键因素,国际上许多国家都趋向选择使用公允价值及现值技术。中国根据国内的实际情况,应选择什么计量基础?能够推行使用公允价值法吗?     

新型两用系363S在泸州育性表现的初步观察

对两用系新资源材料363S在泸州的育性表现进行了初步观察，结果表明：363S在泸州生态条件下，仍表现出明显的“低温诱导不育高温诱导可育”的特点。该不育系正常染色花粉百分率与其小穗育性表现不一致，以小穗育性为标准，在泸州7月中下旬为不育期，小穗不育度99．5％以上。诱导不育和可育的临界温度指标需进一步研究。     

Optimal and efficient crossover designs for comparing test treatments to a control treatment under various models

We study the optimality, efficiency, and robustness of crossover designs for comparing several test treatments to a control treatment. Since A-optimality is a natural criterion in this context, we establish lower bounds for the trace of the inverse of the information matrix for the test treatments versus control comparisons under various models. These bounds are then used to obtain lower bounds for efficiencies of a design under these models. Two algorithms, both guided by these efficiencies and results from optimal design theory, are proposed for obtaining efficient designs under the various models.     

Sample size determination for cluster randomization phase II trials of dichotomous data

One of the main goals for a phase II trial is to screen and select the best treatment to proceed onto further studies in a phase III trial. Under the flexible design proposed elsewhere, we discuss for cluster randomization trials sample size calculation with a given desired probability of correct selection to choose the best treatment when one treatment is better than all the others. We develop exact procedures for calculating the minimum required number of clusters with a given cluster size (or the minimum number of patients with a given number of repeated measurements) per treatment. An approximate sample size and the evaluation of its performance for two arms are also given. To help readers employ the results presented here, tables are provided to summarize the resulting minimum required sample sizes for cluster randomization trials with two arms and three arms in a variety of situations. Finally, to illustrate the sample size calculation procedures developed here, we use the data taken from a cluster randomization trial to study the association between the dietary sodium and the blood pressure.