Exponential smoothing: Behavior of the ex-post sum of squares near 0 and 1

When using simple exponential smoothing on a given time series the nature of the relationship between the optimal smoothing constant and the autocorrelation structure of the series remains an unresolved question. Although numerical search routines can easily be used to find optimal values of the smoothing constant, they offer little insight into the nature of the relationship between the estimated smoothing constant and the structure of the underlying time series. We suggest that renewed investigations of the ex-post sum of squares function may prove helpful in this pursuit. Results are presented that illustrate how the optimal smoothing constant depends upon the value used to initialize the smoothing and upon the sample autocorrelation coefficients of the observed series. These results are based on a new formula for the derivative of the ex-post sum of squares function. In particular, the derivative is examined near 0 and 1, where great simplifications occur in its form, thereby facilitating investigations near these points. A necessary and sufficient condition is stated for when the ex-post sum of squares must have a positive derivative at 0 and the autocorrelation coefficients of the differenced series are shown to affect the sign of the derivative near 1. Based on these results, a general algorithm is presented as an alternative to grid search routines for minimizing the ex-post sum of squares.     

有限和式的积分放缩及应用

本文给出有限和式sum from k=1 to nf(k)的积分放缩的若干结论,并讨论其在求极限、证明不等式和无穷级数收敛性等问题中的应用。     

On some significance tests in cluster analysis

We investigate the properties of several significance tests for distinguishing between the hypothesisH of a homogeneous population and an alternativeA involving clustering or heterogeneity, with emphasis on the case of multidimensional observationsx ₁, ...,x _n ^p . Four types of test statistics are considered: the (s-th) largest gap between observations, their mean distance (or similarity), the minimum within-cluster sum of squares resulting from a k-means algorithm, and the resulting maximum F statistic. The asymptotic distributions underH are given forn and the asymptotic power of the tests is derived for neighboring alternatives.     

Almost sure convergence of weighted sums of NA sequences

For double arrays of constants {a _ni, 1≤i≤k _n, n≥1} and NA r.v. 's {X _n, n≥1}, conditions for almost sure convergence of are given. Both casesk _n ↑ ∞ andk _n=∞ are treated. A Marcinkiewicz-type theorem for i. d. NA sequences is obtained as a special case. Supported by the National Natural Science Foundation of China Cheng Riyan: born in 1968, MS student     

关于宇宙拓扑结构的进一步探索

本文应用宇宙的拓扑模型对宇宙进行分解，从而更进一步地揭示和描述了宇宙的结构：Ｖ＝∪Ｔａ∪Ｑ。     

非线性非高斯模型的高斯和滤波算法

通过将模型的状态噪声和观测噪声均表示成高斯和的形式,推导出非线性非高斯状态空间模型的高斯和递推算法,进一步提出了对应的扩展卡尔曼和滤波器（extended Kalman sum filter, EKSF）和高斯厄密特和滤波器（Gauss-Hermite sum filter, GHSF）。EKSF和GHSF分别用扩展卡尔曼滤波器（extended Kalman filter, EKF）和高斯厄密特滤波器（Gauss-Hermite filter, GHF）作为高斯子滤波器。分析的结果表明,现有的高斯和滤波算法是本文算法的特例;仿真结果表明,EKSF和GHSF能有效处理非线性非高斯模型的状态滤波问题,与高斯和粒子滤波器（Gaussian sum particle filter, GSPF）相比,EKSF和GHSF在保证精度的同时,大大降低了计算量,仿真时间分别约为GSPF的5%和6%。     

洗钱交易模式及其防范分析

基于我国反洗钱监测主要是基于一法二规中的数据报告制度,运用LP方法构建了大额交易洗钱模型.通过对洗钱模型进行仿真及分析,发现了现有大额数据报告制度的缺陷.运用聚类分析方法建立了地区监测模板,并对可疑交易进行了量化界定.最后,对交易监测标准和洗钱模型进行了改进,提出了洗钱的防范措施,以期为提高我国金融机构的监测效率提供一定的借鉴.     

各种速率矢量和激励线性预测（VSELP）编码器的实现

研究并改进了矢量和激励线性预测，语音编码器，介绍了８ｋｂｉｔ／ｓＶＳＥＬＰ编码方案的实现及在此基础上利用矢量量化ＬＰＣ参数，减少激励码本数和子块分裂等方法；改进的６．４ｋｂｉｔ／ｓ，４．８ｋｂｉｔ／ｓ及２．４ｋｂｉｔ／ｓ ＶＳＥＬＰ的方案和结果。     

任意16k阶Franklin完美幻方构造法

提出了一种构造任意16k阶Franklin完美幻方的方法并予以证明.通过讨论Franklin幻方行列各数的对称性,给出了加强及弱化的对称性条件.     

L-Fuzzy拓扑和空间的系列性质

本文研究了L-Fuzzy拓扑和空间的系列性质,揭示了L-Fuzzy拓扑和空间与分明拓扑和空间之间的内在联系.