Quickest Detection of Changes in the Generating Mechanism of a Time Series via the ε-Complexity of Continuous Functions

Abstract

A novel methodology for the quickest detection of abrupt changes in the generating mechanisms (stochastic, deterministic, or mixed) of a time series, without any prior knowledge about them, is developed. This methodology has two components: the first is a novel concept of the ε-complexity and the second is a method for the quickest change point detection (Darkhovsky, 2013 Darkhovsky , B. S. ( 2013 ). Detection of Changes in Random Sequence with Minimum Priori Information, Theory of Probability and Its Applications 58:585–590. (in Russian)  [Google Scholar]). The ε-complexity of a continuous function given on a compact segment is defined. The expression for the ε-complexity of functions with the same modulus of continuity is derived. It is found that, for the Hölder class of functions, there exists an effective characterization of the ε-complexity. The conjecture that the ε-complexity of an individual function from the Hölder class has a similar characterization is formulated. The algorithm for the estimation of the ε-complexity coefficients via finite samples of function values is described. The second conjecture that a change of the generating mechanism of a time series leads to a change in the mean of the complexity coefficients, is formulated. Simulations to support our conjectures and verify the efficiency of our quickest change point detection algorithm are performed.     

Sequential Change-Point Detection and Estimation

Abstract

Two groups of sequential testing procedures are proposed to detect an abrupt change in the distribution of a sequence of observations: truncated and open ended. They are based on large sample strong approximations of the efficient score vector under the null hypothesis of no change and under the alternative hypothesis. An estimator of the time of change is proposed and its approximate bias is analyzed. The estimation of the new parameters that describe the changed distribution naturally follows.     

添加剂对BaO-TiO2-Sm2O3系微波陶瓷改性的研究

研究了影响BaO—TiO2—Sm2O3微波陶瓷材料介电性能的机理，通过用Nd2O3和AL23及MnO2对BaO—TiO2—Sm2O3微波材料进行掺杂改性，得到了二种工艺稳定，品质因素Q值高，τf(谐振频率温度系数)低，烧结温度较低的被波陶瓷材料。该材料可用于制作介质滤波器及分米波通信设备用的小型、轻量的片式元器件。     

香豆素-铜离子(II)配合物硫醇荧光探针的合成及荧光性质的研究

以8-甲酰基-7-羟基香豆素-3-甲酸乙酯与2-氨基苯酚为原料合成了一种亚氨基香豆素类衍生物,其在与铜离子络合后制成了香豆素-铜离子配合物硫醇荧光探针。该探针在体积分数50%的乙醇水溶液中对含有巯基的氨基酸具有良好的选择性。通过荧光光谱,研究了探针的检测机理。在探针识别过程中荧光强度明显增加,在365 nm紫外光激发下荧光颜色由绿色变为蓝色,可以实现可视化检测。     

U-Statistics in Sequential Tests and Change Detection

Abstract

Research on U-statistics within the general framework of sequential and change-point literature is surveyed. Some recent developments are discussed and extended. New sequential testing strategies based on Wiener process approximations are proposed, and empirical studies explore the finite sample performance of these tests. It allows users to choose one that is appropriate for their application.     

PROFILE SUMMARIES FOR ARIMA TIME SERIES MODEL PARAMETERS

Abstract. Autoregressive intergrated moving average (ARIMA) times series models are nonlinear in the parameters and so summarizing the inferential results for such models can be difficult. A common approach is to present parameter joint and marginal inference regions based on the linear approximation, and although such approximate regions are easy to calculate, it is not known generally whether they approximate the true regions adequately. In this paper we present exact approaches for summarizing the inferential results for time series model parameters, called profile t and profile trace plots, which are based on the work of Bates and Watts. Calculations for the profile plots are simple and can be used to determine exact regions, and so can be used to assess the accuracy of linear approximation regions. In addition to developing the profile plots for time series models, the main finding of the paper is that, for ARIMA model parameters, linear approximation regions are very satisfactory except when a parameter estimate is within about two standard errors of the stationarity or invertibility region boundary.     

一种新型耐尔蓝衍生物的合成及其对Hg~(2+)识别研究

设计合成了一种新型耐尔蓝衍生物2-{9-(二甲基氨基)-10-甲基-9H-苯并[a]吩嗪-5-羰基}-N-苯基肼硫代酰胺盐酸盐(EPNH),其结构得到了1HNMR、ESI-MS和元素分析的确认。实验结果表明,该化合物在p H 7.4的HEPES缓冲液中,对Hg2+表现出高选择性和高灵敏度的荧光和显色传感;当Hg2+浓度在0.02~0.25μmol/L范围内时,线性相关系数R=0.997 7,最低检出限为0.01μmol/L(n=6)。     

ESTIMATION OF AUTOREGRESSIVE MOVING-AVERAGE MODELS VIA HIGH-ORDER AUTOREGRESSIVE APPROXIMATIONS

Abstract. In this paper the problem of estimating autoregressive moving-average (ARMA) models is dealt with by first estimating a high-order autoregressive (AR) approximation and then using the AR estimate to form the ARMA estimate. We show how to obtain an efficient ARMA estimate by allowing the order of the AR estimate to tend to infinity as the number of observations tends to infinity. This approach is closely related to the work of Durbin. By transforming the approach into the frequency domain, we can view it as an L ²-norm model approximation of the relative error of the spectral factors. It can also be seen as replacing the periodogram estimate in the Whittle approach by a high-order AR spectral density estimate. Since L ²-norm approximation is a difficult task, we replace it by a modification of a recent model approximation technique called balanced model reduction. By an example, we show that this technique gives almost efficient ARMA estimates without the use of numerical optimization routines.     

Introduction of＂ Ke＂ Series of Spring Wheat Vrieties

“十一五”期间,黑龙江省农业科学院克山分院小麦研究所,依据大兴安岭沿麓优质小麦产业带及黑龙江省不同生态地区的自然条件,选育出了具有代表性的强筋、中强筋品质类型新品种,即克丰11、克丰12、克丰13、克旱21、克春1号和克春2号,在黑龙江省麦区品种的更换中发挥了重要的作用。该文着重介绍上述6个新品种的农艺性状、品质特性、产量水平以及栽培要点和适宜种植区域,期望有助于全面了解、快速推广应用。     

一种原油储罐界面参数的快速检测方法及其实现

针对原油储罐多液位界面参数测量中数据处理存在的问题,提出了基于递归累积和序列数据拐点检测原理的界面参数分析方法。该方法利用多液位界面参数测量仪采集的序列数据,递归地调用基于累积和的序列拐点检测算法,利用拐点数据的特性作为储罐内部多种介质的分界点,从而判定多液位界面参数的具体信息。