On Fan's adaptive Neyman tests for comparing two spectral densities

In this paper, we consider tests for assessing whether two stationary and independent time series have the same spectral densities (or same autocovariance functions). Both frequency domain and time domain test statistics for this purpose are reviewed. The adaptive Neyman tests are then introduced and their performances are investigated. Our tests are adaptive, that is, they are constructed completely by the data and do not involve any unknown smoothing parameters. Simulation studies show that our proposed tests are at least comparable to the current tests in most cases. Furthermore, our tests are much more powerful in some cases, such as against the long orders of autoregressive moving average (ARMA) models such as seasonal ARMA series.     

Short run spc based upon the second order dynamic linear model for trend detection

Recently, several new applications of control chart procedures for short production runs have been introduced. Bothe (1989) and Burr (1989) proposed the use of control chart statistics which are obtained by scaling the quality characteristic by target values or process estimates of a location and scale parameter. The performance of these control charts can be significantly affected by the use of incorrect scaling parameters, resulting in either an excessive "false alarm rate," or insensitivity to the detection of moderate shifts in the process. To correct for these deficiencies, Quesenberry (1990, 1991) has developed the Q-Chart which is formed from running process estimates of the sample mean and variance. For the case where both the process mean and variance are unknown, the Q-chaxt statistic is formed from the standard inverse Z-transformation of a t-statistic. Q-charts do not perform correctly, however, in the presence of special cause disturbances at process startup. This has recently been supported by results published by Del Castillo and Montgomery (1992), who recommend the use of an alternative control chart procedure which is based upon a first-order adaptive Kalman filter model Consistent with the recommendations by Castillo and Montgomery, we propose an alternative short run control chart procedure which is based upon the second order dynamic linear model (DLM). The control chart is shown to be useful for the early detection of unwanted process trends. Model and control chart parameters are updated sequentially in a Bayesian estimation framework, providing the greatest degree of flexibility in the level of prior information which is incorporated into the model. The result is a weighted moving average control chart statistic which can be used to provide running estimates of process capability. The average run length performance of the control chart is compared to the optimal performance of the exponentially weighted moving average (EWMA) chart, as reported by Gan (1991). Using a simulation approach, the second order DLM control chart is shown to provide better overall performance than the EWMA for short production run applications     

Statistical Inference of Adaptive Designs with Binary Responses

Adaptive designs of clinical trials are ethical alternatives when the traditional randomization becomes ethically infeasible in desperate medical situations. However, such a design creates a dependency among trial data and its statistical analysis becomes more complex than the analysis for traditional randomized clinical trials. In this article, we examine adaptive designs with dichotomous responses from two treatments and extend some commonly used statistical methods for independent data. Under a regularity condition, the estimated odds ratio and its logarithm are shown to follow asymptotically normal distributions. Moreover, the ordinary goodness-of-fit test statistic for two-by-two contingency tables with dependent data is shown to be asymptotically chi-square distributed. We also discuss the consistency of maximum likelihood estimators of the unknown parameters for a wide class of adaptive designs.     

论适应性表征及其方法论意义

适应性是主体适应其环境的特性,是物理演化系统和生物演化系统的本质属性,反映在认知上就是适应性表征。适应性表征也因此成为知识显现的方式和创造的核心,具有协调性、匹配性、互补性、模拟性和类比性,其表现方式有直接具象表征、间接具象表征、直接抽象表征和间接抽象表征,分别对应于经验主义、建构经验主义、理性主义和科学实在论。适应性表征的实现是通过科学理论核心概念的变化、定律的凝练、理论的更替、模型推理和世界观的改变展开的,具有经验上的适当性。这种经验适当性不仅是感知层次的体验,更是一种认知模式。在认知意义上,经验也是基于心理模型的,心理建模的路径有思想语言、心理表象、心理命题、思想实验和心理模拟推理。这种基于心理建模的适应性表征为科学认知和科学发现提供了有益的方法论。     

变革社会中的政治资源配置

政治资源配置是变革社会中的一个重要发展参数。社会转型时期 ,既有政治资源的配置结构有所松动 ,出现分散性发展的倾向 ,而其既有之高度集中性也愈益显示某些弊端。因应形势的变化 ,中国共产党有必要引导政治资源配置作出适应性调整 ,促使其向合理性和适度社会倾向性变革 ,并增强自身开发、掌用政治资源的能力 ,确保党在政治资源配置中的主导地位     

Random variate transformations in the Gibbs sampler: issues of efficiency and convergence

In the non-conjugate Gibbs sampler, the required sampling from the full conditional densities needs the adoption of black-box sampling methods. Recent suggestions include rejection sampling, adaptive rejection sampling, generalized ratio of uniforms, and the Griddy-Gibbs sampler. This paper describes a general idea based on variate transformations which can be tailored in all the above methods and increase the Gibbs sampler efficiency. Moreover, a simple technique to assess convergence is suggested and illustrative examples are presented.     

企业战略与环境的适应性:一个复杂适应系统的视角

企业战略的重要特性之一是它对环境的适应性,它强调企业组织能够运用自己的资源去适应组织外部环境和内在条件的变化。企业环境是不确定的,面对不同层次的不确定性环境,企业的适应性战略主要包括外包战略、联盟战略、柔性战略。     

HF通信网中的突发自适应选频技术

介绍了突发自适应选频技术在ＨＦ通信网中的应用，分析了突发自适应选频的特点及网络应用的优势，设计了一套用于网络突发选频的协议，讨论了协议中的重要参数设定和协议性能，并提出了多种方案供优化     

HDTV信源编码中的自适应处理

在序列图像编码中，自适应性是提高图像主观质量的一个关键，自适应处理方法一般是窈门（ｋｎｏｗ－ｈｏｗ）的形式出现，它是从编码的实践中获得的。讨论了人的视觉特性及如何将它用于对ＤＣＴ系数的量化，以改善ＨＤＴＶ序列解码象的主观质量。实验表明，文中所述方法的解码图像的主观质量比作者在文献［１］中报告的有明显改善。