Reml and best linear unbiased prediction in state space models

This article takes a hierarchical model approach to the estimation of state space models with diffuse initial conditions. An initial state is said to be diffuse when it cannot be assigned a proper prior distribution. In state space models this occurs either when fixed effects are present or when modelling nonstationarity in the state transition equation. Whereas much of the literature views diffuse states as an initialization problem, we follow the approach of Sallas and Harville (1981,1988) and incorporate diffuse initial conditions via noninformative prior distributions into hierarchical linear models. We apply existing results to derive the restricted loglike-lihood and appropriate modifications to the standard Kalman filter and smoother. Our approach results in a better understanding of De Jong's (1991) contributions. This article also shows how to adjust the standard Kalman filter, the fixed inter- val smoother and the state space model forecasting recursions, together with their mean square errors, for he presence of diffuse components. Using a hierarchical model approach it is shown that the estimates obtained are Best Linear Unbiased Predictors (BLUP).     

Non-Gaussian Ornstein–Uhlenbeck-based models and some of their uses in financial economics

Non-Gaussian processes of Ornstein–Uhlenbeck (OU) type offer the possibility of capturing important distributional deviations from Gaussianity and for flexible modelling of dependence structures. This paper develops this potential, drawing on and extending powerful results from probability theory for applications in statistical analysis. Their power is illustrated by a sustained application of OU processes within the context of finance and econometrics. We construct continuous time stochastic volatility models for financial assets where the volatility processes are superpositions of positive OU processes, and we study these models in relation to financial data and theory.     

Smoothing a Time Series by Segments of the Data Range

We consider the problem of estimating a trend with different amounts of smoothness for segments of a time series subjected to different variability regimes. We propose using an unobserved components model to consider the existence of at least two data segments. We first fix some desired percentages of smoothness for the trend segments and deduce the corresponding smoothing parameters involved. Once the size of each segment is chosen, the smoothing formulas here derived produce trend estimates for all segments with the desired smoothness as well as their corresponding estimated variances. Empirical examples from demography and economics illustrate our proposal.     

Smoking Prevalence and Antismoking Regulations in Transition Countries

As a number of new nations emerged in the early nineties, there has been a spurt in regulatory initiatives in transition countries toward nation building and socio-economic reforms. A key prerequisite to policy changes is an understanding of the related patterns and policies. This paper provides an overview of the smoking trends in transition nations, broken by gender and age, and the antismoking policies in place. In particular, four different types of non-price policies are studied. Comparisons with the rest of the world show that transition countries do not fare badly in terms of implementing antismoking policies and are, in fact, better in some cases than other countries. However, greater smoking prevalence for some population subgroups in transition nations suggests that either some other socio-economic factors influencing smoking prevalence might be at play or there might be some enforcement issues with the policies in place.     

波前滤波小波函数的理论分析和构造方法

从惠更斯-菲涅耳的衍射理论出发．分析了受限孔径衍射相当于波前滤波．以夫琅和费单缝、圆孔为例．得到了小波在波前滤波时应满足的条件．并给出了满足波前滤波条件的小波的构造方法．     

用余弦调制PR－FIR方法构造M带正交小波基

离散小波变换将离散时间信号分解为一系列不同分辨率下的离散近似信号和离散细节，紧支的正交规范小波与完全重构正交镜像滤波器（ＰＲ－ＱＭＦ）相对应。在紧支正交小波基的构造条件下，利用余弦调制完全重构滤波器组的方法，实现了Ｍ带紧支正交小波基的构造，计算机模拟表明该方法非常简单、有效。     

一种瞬变步长LMS自适应滤波算法

基于规一化起动、平滑递推和ＰＬＳ算法导出了一种新的变步长ＬＭＳ算法。文中分析了起动后的平稳连接和提高起始收敛速度的条件，证明了步长因子μ（ｋ）的瞬变特性及其对减小失调噪声的作用。计算机仿真效果较好，支持了理论分析。     

SPLINE SMOOTHER AS A DYNAMIC LINEAR MODEL

The paper shows how a finite dimensional representation of a cubic smoothing spline can be put in the framework of a dynamic linear model. The formulation provides an updating scheme when observations do not occur sequentially in time or space.     

DELAY ESTIMATION BY A HILBERT TRANSFORM METHOD

This paper describes an estimation of the time delay between two stationary time series signals, in which an input signal is measured with little noise and an output signal is the sum of a noise and the response from a linear system. We use the Hilbert transform relation for minimum delay systems to estimate the time delay. Some computer simulation results are given to evaluate the performance of the proposed method.