An alternative to ratio method in sample surveys

Summary This paper examines a simple transformation which enables the use of product method in place of ratio method. The convenience with the former, proposed by Murthy [3], is that expressions for bias and mean square error (mse) can be exactly evaluated. The optimum situation in the minimum mse sense and allowable departures from this optimum are indicated. The procedure requires a good guess of a certain parameter, which does not seem very restrictive for practice. Two methods for dealing with the bias of the estimator are mentioned. An extension to use multiauxiliary information is outlined.     

Utility function assessment on a micro-computer: An interactive procedure

The procedure UFAP is presented which allows a decision maker to interactively assess his von Neumann/Morgenstern single attribute utility function. UFAP puts special emphasis on potential biases in the assessment process. In the first part of the procedure three different assessment methods are used to derive ranges for the utility function. Using different methods enables us to point out a possible bias in the elicitation process. In the second part a consistent class of utility functions is derived based on the ranges assessed in the first part. In case inconsistencies between methods arise the decision maker has to reconsider selected preference statements previously given.     

Distributional Transformations,Orthogonal Polynomials,and Stein Characterizations

A new class of distributional transformations is introduced, characterized by equations relating function weighted expectations of test functions on a given distribution to expectations of the transformed distribution on the test functions higher order derivatives. The class includes the size and zero bias transformations, and when specializing to weighting by polynomial functions, relates distributional families closed under independent addition, and in particular the infinitely divisible distributions, to the family of transformations induced by their associated orthogonal polynomial systems. For these families, generalizing a well known property of size biasing, sums of independent variables are transformed by replacing summands chosen according to a multivariate distribution on its index set by independent variables whose distributions are transformed by members of that same family. A variety of the transformations associated with the classical orthogonal polynomial systems have as fixed points the original distribution, or a member of the same family with different parameter.     

Asymptotic bias of the least squares estimator for multivariate autoregressive models

Summary The asymptotic bias of the least squares estimator for the multivariate autoregressive models is derived. The formulas for the low order univariate autoregressive models are given in terms of the simple functions of parameters. Our results are useful to the bias correction method of the least squares estimation. This work was supported by National Science Foundation Grant SES79-13976 at the Institute for Mathematical Studies in the Social Sciences, Stanford University. This paper is a revision of Discussion Paper No. 504, The Center for Mathematical Studies in Economics and Management Science, Northwestern University, October 1981.     

源、漏到栅距离对次亚微米ggNMOS ESD保护电路鲁棒性的影响

基于对静电放电(electrostatic discharge,ESD)应力下高电压、大电流特性的研究,本文通过优化晶格自加热漂移-扩散模型和热力学模型,并应用优化模型建立了全新的0.6 μm CSMC 6S06DPDM-CT02 CMOS工艺下栅接地NMOS (gate grounded NMOS,ggNMOS)ESD保护电路3D模型,对所建模型中漏接触孔到栅距离(drain contact to gate spacing,DCGS)与源接触孔到栅距离(source contact to gate sp 关键词： 栅接地NMOS 静电放电 漏接触孔到栅的距离 源接触孔到栅的距离     

飞秒激光制备硅窗口增透保护类金刚石膜

采用飞秒激光(800 nm,120 fs,3 W,1 000 Hz)制备类金刚石膜,研究了不同偏压、生长温度和氧气氛等辅助手段对激光沉积类金刚石膜的影响,实验发现在室温(25℃)、无偏压和低气压氧气氛(2 Pa)条件下沉积的类金刚石膜性能最优。在单面预镀普通增透膜的硅红外窗口材料上镀制出了无氢类金刚石膜,3~5μm波段平均透过率达到90%以上,纳米硬度高达40 GPa,用压力为9.8 N的橡皮磨头,摩擦105次,膜层未见磨损,并且通过了军标规定的高温、低温、湿热、盐雾等环境试验,所制类金刚石膜可对红外窗口起到较好的增透保护作用。     

Effects of component ratio and easy axes distribution on the exchange bias in ferromagnetic-antiferromagnetic random alloys

For a ferromagnetic (FM)-antiferromagnetic (AFM) system with composition x(FM)+(AFM)_1−x, a modified Monte Carlo Metropolis method is performed to study the effects of x and easy axes distribution at the FM/AFM nearest neighbors on exchange bias field H_E, coercivity H_C, and vertical magnetization shift M_E after cooling under different magnetic fields h_CF. When the orientations of easy axes are uniform, the x dependence of H_E and M_E undergo a non-monotonous to monotonous process with the increase of h_CF, whereas H_C shows a more complex behavior. On the other hand, for the case of the random orientation, H_C has a peak around x=0.5, while M_E decreases with the increase of x. H_E exhibits negative extrema at small x and disappears for larger x. However, abnormal positive H_E observed depends on the frustration and the distinct trends of two coercive fields with x in such a special model.     

加速方程有偏场合下加速寿命试验的稳健设计

考虑在加速寿命试验中,当假定的加速模型不是转化应力的线性模型时,模型参数的极大似然估计的近似分布。研究在一定的条件下,获得正常应力下寿命分布的p分位寿命估计的最优稳健设计方法。并通过数值例子说明方法的有效性。     

On the non-equivalence of two standard random walks

We focus on two models of nearest-neighbour random walks on d$d$-dimensional regular hyper-cubic lattices that are usually assumed to be identical—the discrete-time Polya walk, in which the walker steps at each integer moment of time, and the Montroll–Weiss continuous-time random walk in which the time intervals between successive steps are independent, exponentially and identically distributed random variables with mean 1$1$. We show that while for symmetric random walks both models indeed lead to identical behaviour in the long time limit, when there is an external bias they lead to markedly different behaviour.     

A Monte Carlo-Adjusted Goodness-of-Fit Test for Parametric Models Describing Spatial Point Patterns

Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for the Monte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided. We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online.