一元整系数多项式一个结论的推广应用

将一元整系数多项式有理根的一个结论在多元多项式上进行了推广,从而得到多元多项式因式分解的一种方法。     

Measuring agreement between two statistics with applications to age standardization

Summary.  We detail a general method for measuring agreement between two statistics. An application is two ratios of directly standardized rates which differ only by the choice of the standard. If the statistics have a high value for the coefficient of agreement then the expected squared difference between the statistics is small relative to the variance of the average of the two statistics, and inferences vary little by changing statistics. The estimation of a coefficient of agreement between two statistics is not straightforward because there is only one pair of observed values, each statistic calculated from the data. We introduce estimators of the coefficient of agreement for two statistics and discuss their use, especially as applied to functions of standardized rates.     

ASSESSING CONGRUENCEAMONG DISTANCE MATRICES: SINGLE-MALT SCOTCH WHISKIES REVISITED

A test of congruence among distance matrices is described. It tests the hypothesis that several matrices, containing different types of variables about the same objects, are congruent with one another, so they can be used jointly in statistical analysis. Raw data tables are turned into similarity or distance matrices prior to testing; they can then be compared to data that naturally come in the form of distance matrices. The proposed test can be seen as a generalization of the Mantel test of matrix correspondence to any number of distance matrices. This paper shows that the new test has the correct rate of Type I error and good power. Power increases as the number of objects and the number of congruent data matrices increase; power is higher when the total number of matrices in the study is smaller. To illustrate the method, the proposed test is used to test the hypothesis that matrices representing different types of organoleptic variables (colour, nose, body, palate and finish) in single‐malt Scotch whiskies are congruent.     

GPS接收机P(Y)直捕方法研究

GPS接收机P(Y)直捕算法是基于存储的滑动相关搜索,并利用FFT将时频二维联合搜索变成时域一维搜索。同时,考虑位同步点已知的条件,接收资源池只需存储一段接收序列,缩短了捕获时间且利于硬件实现。仿真结果表明,多普勒频移为±5kHz时,所带来的峰值衰减为2dB左右,本地信号与接收信号对齐时出现明显的相关峰,很好地实现了捕获功能;提出了用重叠分段补零FFT操作实现并行相关,成倍降低了捕获时间;提出了利用位同步信息,避免了码极性翻转可能引起的信噪比损耗;针对码相位漂移,提出了优化捕获策略,可在短时间内完成重捕。     

采用二阶特征窗的语音盲分离方法

利用语音信号的短时平稳特性,提出了一种二阶特征窗语音盲分离方法。该方法采用新的联合差分相关矩阵白化算法去除有色噪声影响;用长度等于语音信号基音周期的等距特征窗连续分割预白化观测数据,在每个加窗的数据帧计算不同的时滞协方差矩阵。利用联合近似对角化时滞协方差矩阵集合得到旋转参数,最终达到语音信号的盲分离。该方法消除了有色噪声的影响,只需用到二阶信息就能很好地分离语音信号。仿真实验验证了该方法的有效性。     

Backfitting Random Varying-Coefficient Models with Time-Dependent Smoothing Covariates

Abstract.  In this paper, we propose a random varying-coefficient model for longitudinal data. This model is different from the standard varying-coefficient model in the sense that the time-varying coefficients are assumed to be subject-specific, and can be considered as realizations of stochastic processes. This modelling strategy allows us to employ powerful mixed-effects modelling techniques to efficiently incorporate the within-subject and between-subject variations in the estimators of time-varying coefficients. Thus, the subject-specific feature of longitudinal data is effectively considered in the proposed model. A backfitting algorithm is proposed to estimate the coefficient functions. Simulation studies show that the proposed estimation methods are more efficient in finite-sample performance compared with the standard local least squares method. An application to an AIDS clinical study is presented to illustrate the proposed methodologies.     

两个随机变量的独立性和相关性之比较

从随机变量的独立性和相关性概念出发,运用反例和定理的形式详细探讨二者的区别和联系.     

将分段函数表示为初等函数的方法

本文给出了一种化具有多个分段点，且在各区间段上的表达式为多项式函数的分段函数为初等函数的具体方法．     

基于因果关系的教育研究方法思考

探索、检验因果关系是教育科学研究的重要目标之一,相关分析、回归分析、路径分析等常用统计方法存在许多不足。结构方程模型是针对这些不足提出来的,从统计思路上,它具有优点,但还不够完善,应引起我国教育学界的注意。     

Geometric Method and Generalized Linear Models. Two Opposite Multiparametric Approaches Illustrated on a Sample of Pituitary Adenomas

We used two statistical methods to identify prognostic factors: a log-linear model (logistic and COX regression, based on the notions of linearity and multiplicative relative risk), and the CORICO method (ICOnography of CORrelations) based on the geometric significance of the correlation coefficient. We applied the methods to two different situations (a "case-control study' and a "historical cohort'). We show that the geometric exploratory tool is particularly suited to the analysis of small samples with a large number of variables. It could save time when setting up new study protocols. In this instance, the geometric approach highlighted, without preconceived ideas, the potential role of multihormonality in the course of pituitary adenoma and the unexpected influence of the date of tumour excision on the risk attached to haemorrhage.