A Constrained Interval-Valued Linear Regression Model: A New Heteroscedasticity Estimation Method

Linear regression models for interval-valued data have been widely studied. Most literatures are to split an interval into two real numbers, i.e., the left- and right-endpoints or the center and radius of this interval, and fit two separate real-valued or two dimension linear regression models. This paper is focused on the bias-corrected and heteroscedasticity-adjusted modeling by imposing order constraint to the endpoints of the response interval and weighted linear least squares with estimated covariance matrix, based on a generalized linear model for interval-valued data. A three step estimation method is proposed. Theoretical conclusions and numerical evaluations show that the proposed estimator has higher efficiency than previous estimators.

     

Adjusted Empirical Likelihood Estimation of Distribution Function and Quantile with Nonignorable Missing Data

This paper considers the estimation problem of distribution functions and quantiles with nonignorable missing response data. Three approaches are developed to estimate distribution functions and quantiles, i.e., the Horvtiz-Thompson-type method, regression imputation method and augmented inverse probability weighted approach. The propensity score is specified by a semiparametric exponential tilting model. To estimate the tilting parameter in the propensity score, the authors propose an adjusted empirical likelihood method to deal with the over-identified system. Under some regular conditions, the authors investigate the asymptotic properties of the proposed three estimators for distribution functions and quantiles, and find that these estimators have the same asymptotic variance. The jackknife method is employed to consistently estimate the asymptotic variances. Simulation studies are conducted to investigate the finite sample performance of the proposed methodologies.     

Estimation in Partially Observed Functional Linear Quantile Regression

Currently, working with partially observed functional data has attracted a greatly increasing attention, since there are many applications in which each functional curve may be observed only on a subset of a common domain, and the incompleteness makes most existing methods for functional data analysis ineffective. In this paper, motivated by the appealing characteristics of conditional quantile regression, the authors consider the functional linear quantile regression, assuming the explanatory f...     

控制系统故障检测与多模型混合估计方法

讨论了现有控制系统故障检测与诊断方法中存在的问题,指出了基于多模型估计理论的系统故障检测是一种值得注意的发展方向,简要说明了多模型估计方法的基本原理,介绍了交互式多模型混合估计方法在控制系统故障检测与诊断中的具体应用技术,分析了多模型混合估计理论的发展方向.     

Two-Stage Online Debiased Lasso Estimation and Inference for High-Dimensional Quantile Regression with Streaming Data

In this paper, the authors propose a two-stage online debiased lasso estimation and statistical inference method for high-dimensional quantile regression(QR) models in the presence of streaming data. In the first stage, the authors modify the QR score function based on kernel smoothing and obtain the online lasso smoothed QR estimator through iterative algorithms. The estimation process only involves the current data batch and specific historical summary statistics, which perfectly accommodates ...     

Consistent Estimation of Order for Regression in the Presence of Serial Correlation and Heteroscedasticity

1　 IntroductionIn econometric regression models,serial correlation and heteroscedasticity are twocommonly encoutered features of disturbance behavior and may often occursimultaneously. For example,the effects of omitted variables may give rise to bothproblems simultaneously.Therefore,an econometric regression model where both serialcorrelation and heteroscedasticity are present would be feasible.There are literaturesconcerning efficient estimation of regressions with both serial correlation a…     

Single-Index Quantile Regression with Left Truncated Data

The purpose of this paper is two fold. First, the authors investigate quantile regression(QR) estimation for single-index QR models when the response is subject to random left truncation.The random weights are introduced to deal with left truncated data and the associated iteration estimation method is proposed. The asymptotic properties for the proposed QR estimates of the index parameter and unknown link function are both obtained. Further, by combining the QR loss function and the adaptive LA...     

信号故障检测的自相关方法

本文将信号的自相关特性应用到故障检测中,给出了故障检测的表达式,分别讨论了两类信号的故障检测实现方法,还给出了检测故障的算法。仿真结果表明,自相关方法用于故障检测是可行的。该方法可应用到设备内部自测试中,并可完成周期信号的在线故障检测。     

一种摄像机姿态估计方法

提出一种摄像机姿态估计方法,线性确定摄像机姿态及标定相机矩阵。将n个控制点组成n-1个独立矢量,根据成像过程,构建起基于矢量运算的摄像机姿态和相机矩阵的线性约束方程。依据线性理论,及旋转阵R的正交性化简、表达约束方程,通过矢量运算给出摄像机姿态和相机矩阵的解析解,模拟和真实实验都验证了该方法的有效性。     

非合作双基地雷达互相关时差估计仿真分析

根据非合作双基地雷达系统的特点,讨论了非合作双基地雷达的基本几何关系与信号能量关系,提出了采用中频数字化技术在频域上实现参考通道与目标通道的快速互相关检测的方法,并在仿真实验中模拟了噪声背景中直达波与目标散射回波的互相关检测与时差估计的过程,实验表明该方法能够在参考通道与目标通道的信噪比相差十分悬殊的情况下,有效地完成微弱目标的检测.蒙特·卡罗仿真分析了信噪比、信号脉宽、带宽和相关脉冲数对互相关时差估计性能的影响.     

基于FFT相位差的载波估计算法仿真与改进

由于栅栏效应,直接用FFT估计频率和相位仅能获得非常粗的精度。精确的估计需要在FFT谱线基础上做进一步的插值等运算。文献[1,2]提出了基于FFT相位差的载波频率和相位估计算法,利用两段FFT谱线间的相位差消除了栅栏效应的影响,获得了精确的估计。但经过仿真,该文献提出的方法估计性能依赖于所估计信号的频率,在某些频率点能获得很好的估计性能,但在少数频率点附近性能恶化严重。对该问题进行了理论分析,找出性能恶化的原因所在并提出了改进办法,克服了原文献算法的缺点。仿真表明,在整个频率动态范围内,改进后算法都非常稳定,具有很好的估计性能。同时改进后算法同样运算简单,便于实现。     

Hall分布族在巨额索赔数据的极值分位数估计与风险度量中的应用

基于指数回归模型构造了厚尾分布的一个子族——Hall分布族的极值分位数估计,并将该方法应用于巨额索赔数据进行了实证分析。然后,对巨灾保险进行了风险度量,得到了该数据的极值分位数,并作出了合理解释。     

具有一种新的图像雅可比矩阵估计方法的无定标视觉伺服

对于基于图像的具有手眼或固定摄像机模式的视觉伺服,考虑机器人的运动学及动力学特性,在摄像机的内外参数未知的情况下,提出了一种直接自适应控制方案实现位置控制或轨迹跟踪;利用矩阵变换的方法使得图像雅可比矩阵的组成元素线性地出现在闭环动力学方程中,从而设计了一种新的自适应估计方法在线估计图像雅可比矩阵;利用李亚普诺夫的方法证明了图像误差的渐近收敛性。仿真结果验证了该方法的有效性。     

一种参数估计方法及其在可靠性增长分析中的应用

在可靠性增长分析中,研究Gompertz模型,Duane模型和AMSAA模型的参数点估计方法的文献有很多。本文应用微分回归方法,获得了上述模型参数的又一种点估计,其优点在于:点估计的表达式能显式给出且计算简便。     

Empirical Likelihood Based Diagnostics for Heteroscedasticity in Semiparametric Varying-Coefficient Partially Linear Models with Missing Responses

Journal of Systems Science and Complexity - This paper proposes an empirical likelihood based diagnostic technique for heteroscedasticity for semiparametric varying-coefficient partially linear...     

移动通信信号到达时间差定位的估计

到达时间差(TimeDifferenceofArrival,TDOA)位置估计是无线定位的一项关键技术.首先介绍了TDOA定位估计原理,阐述了基站任意分布时(以三基站为例)的二维定位估计,以及在特殊情况下,即基站线性分布时的定位估计.最后,对三基站TDOA定位估计及其定位精度进行了仿真,为第三代移动通信无线定位系统的研究和开发提供了理论基础.     

一种基于导频的OFDM系统信道估计方法

提出一种使用矩形导频图案的OFDM信道估计方法。接收端首先在频率方向估计信道,然后在时间方向插值。该方法仅需累加和少量乘法运算就能估计出信道冲激响应,复杂度低,实时性高。在未编码16QAM-OFDM系统中,通过仿真将提出的方法与线性、cubic和MMSE插值法进行均方误差和误比特率的比较。结果表明该方法性能优于前两者,接近后者。     

基于分位数回归的样条函数法拟合国债利率期限结构

通过引入分位数回归的方法,用多项式样条拟合上交所国债市场的利率期限结构,获得了一个稳健的估计,并有效地识别出错误定价的债券.     

一种基于解压的镜头探测方法

镜头探测是视频内容和结构化分析的第一步。目前的镜头探测方法根据处理角度不同 ,主要分为压缩域和解压域两种。提出了一种基于解压的镜头探测方法。该方法基于这样一个假定 ,即同一镜头往往具有相同的背景区域。通过对背景区域的数据进行分析 ,得到视频的镜头边界。该方法具有设置参数少、阈值敏感度低以及处理数据量小的特点 ,适用于大容量的视频库。通过对各种不同类型的视频进行实验 ,证明该方法具有较强的适应性和鲁棒性 ,可以获得较高的镜头查到率和查准率     

噪声中相参脉冲的检测和参数提取

分析了使用自相关和反向预测技术从被噪声淹没的信号中检测出信噪比,以判定有无雷达信号存在的方法.分析了利用接收到的雷达直接辐射信号找出由目标反射的雷达信号的延迟时间,以及反射信号能量的互相关方法.最后,以仿真例子验证了分析结果的正确性,进而说明了这两种技术在低截获概率雷达侦察和仿多基地雷达机制的被动定位方面的应用前景.