Spatial Nonparametric Regression Estimation: Non-isotropic Case

Data collected on the surface of the earth often has spatial interaction. In this paper, a non-isotropic mixing spatial data process is introduced, and under such a spatial structure a nonparametric kernel method is suggested to estimate a spatial conditional regression. Under mild regularities, sufficient conditions are derived to ensure the weak consistency as well as the convergence rates for the kernel estimator. Of interest are the following: (1) All the conditions imposed on the mixing coefficient and the bandwidth are simple; (2) Differently from the time series setting, the bandwidth is found to be dependent on the dimension of the site in space as well; (3) For weak consistency, the mixing coefficient is allowed to be unsummable and the tendency of sample size to infinity may be in different manners along different direction in space; (4) However, to have an optimal convergence rate, faster decreasing rates of mixing coefficient and the tendency of sample size to infinity along each direction a     

时域近场测量的间接频域算法和直接时域算法研究

时域近远场变换是时域近场天线测量的关键技术。本文对时域近远场变换的间接频域算法和直接时域算法进行了数值模拟和分析。针对开口矩形波导天线的时域近场测量 ,选取时空采样参数和内插公式 ,用两种算法计算时域远场方向图 ,分析周期性、时域混叠问题和扫描面截断效应 ,在相互比较和验证的基础上 ,指出两者的优、缺点及适用的情况。     

Estimation of the Common Mean of a Bivariate Normal Population

In this paper we discuss the problem of estimating the common mean of a bivariate normal population based on paired data as well as data on one of the marginals. Two double sampling schemes with the second stage sampling being either a simple random sampling (SRS) or a ranked set sampling (RSS) are considered. Two common mean estimators are proposed. It is found that under normality, the proposed RSS common mean estimator is always superior to the proposed SRS common mean estimator and other existing estimators such as the RSS regression estimator proposed by Yu and Lam (1997, Biometrics, 53, 1070–1080). The problem of estimating the mean Reid Vapor Pressure (RVP) of regular gasoline based on field and laboratory data is considered.     

用于ICF驱动器的取样光栅的矢量分析与计算

 在ICF的终端光学聚焦系统中，采用取样光栅(BSG)将透射的三倍频光按一定比例送入能量计中进行能量诊断。本文采用精确耦合波矢量分析方法分析了衍射效率与光栅周期、刻槽深度、占空比等的关系，为光栅的实际制作提供了一些有意义的结果。     

Asymptotic analysis of stochastic programs

In this paper we discuss a general approach to studying asymptotic properties of statistical estimators in stochastic programming. The approach is based on an extended delta method and appears to be particularly suitable for deriving asymptotics of the optimal value of stochastic programs. Asymptotic analysis of the optimal value will be presented in detail. Asymptotic properties of the corresponding optimal solutions are briefly discussed.     

The effect of head position on glottic closure in patients with unilateral vocal fold paralysis

The present study was designed to assess the effect of head position on glottic closure as reflected in airflow rates (open quotient and maximum flow declination rate), in patients with unilateral vocal fold paralysis. Ten patients, 2 males and 8 females ranging in age from 40 to 75, with a mean age of 57.3, served as subjects. Airflow measures were taken during sustained phonation of two vowels (/i/ and /a/) in 3 head positions (center, right, left). Vowels /i/ and /a/ were produced at subject's comfortable pitch and loudness, with random ordering of both vowel order and head orientation. Subjects were trained to focus eye gaze on right and left markers (70-degree angle) and a central marker at eye level directly in front of the subject. Theoretically, if turning the head during phonation alters the laryngeal anatomic relationship by bringing the vocal folds in closer proximity to one another, then airflow rate should lessen. Our results indicate that head position does not improve glottic closure in these patients, which is in contrast to previously published research.(1) Our results question the utility and underlying theoretical construct for the use of head turning as a therapeutic technique for improvement of voice in patients with unilateral vocal fold paralysis.     

Estimating household purchase rates for consumer nondurable goods

Understanding the purchase rates of households for frequently purchased packaged goods is an important element in developing effective marketing strategies. Previous researchers have attempted to estimate these rates by assuming that the time between purchases is a random variable that follows some common parametric probability distribution such as the exponential or Weibull distribution. Recent research has shown that for many frequently purchased packaged goods, the interpurchase times cannot be adequately described by these commonly used probability distributions. In this study we demonstrate how household purchase rates can be estimated in a robust manner using a generalized semiparametric approach that obviates the need for specifying a parametric form for the distribution of interpurchase times. The motivation being that often there is no theory of household purchase behaviour that specifies a priori the probability distribution underlying the interpurchase times. Our empirical results indicate that, for the data analysed, the household purchase rates exhibit a regular pattern that cannot be recovered by probability distributions often used in previous research. Further, marketing actions taken by sellers do indeed influence household purchase behaviour.     

利用辅助样本时系统抽样方差的非负无偏估计

该文主要考虑按一般的抽样方案抽取辅助样本时系统抽样方差的非负无偏估计，统一了相关的结果．     

Approximation of weak sense stationary stochastic processes from local averages

We show that a weak sense stationary stochastic process can be approximated by local averages. Explicit error bounds are given. Our result improves an early one from Splettstosser.     

Least Squares Convex-Concave Data Smoothing

We consider n noisy measurements of a smooth (unknown) function, which suggest that the graph of the function consists of one convex and one concave section. Due to the noise the sequence of the second divided differences of the data exhibits more sign changes than those expected in the second derivative of the underlying function. We address the problem of smoothing the data so as to minimize the sum of squares of residuals subject to the condition that the sequence of successive second divided differences of the smoothed values changes sign at most once. It is a nonlinear problem, since the position of the sign change is also an unknown of the optimization process. We state a characterization theorem, which shows that the smoothed values can be derived by at most 2n – 2 quadratic programming calculations to subranges of data. Then, we develop an algorithm that solves the problem in about O(n ²) computer operations by employing several techniques, including B-splines, the use of active sets, quadratic programming and updating methods. A Fortran program has been written and some of its numerical results are presented. Applications of the smoothing technique may be found in scientific, economic and engineering calculations, when a potential shape for the underlying function is an S-curve. Generally, the smoothing calculation may arise from processes that show initially increasing and then decreasing rates of change.