A LINEAR ESTIMATION PROCEDURE FOR THE PARAMETERS OF AUTOREGRESSIVE MOVING-AVERAGE PROCESSES

Abstract. A linear estimation procedure for the parameters of autoregressive moving-average processes is proposed. The basic idea is to write the spectrum for the moving-average part as a linear function of a properly selected set of parameters and to use Chiu's weighted least-squares procedure to reduce the problem to a weighted linear least-squares problem. The proposed procedure finds estimates by solving systems of linear equations and does not need optimization programs. An one-step estimate is also suggested. It is shown that the estimates are asymptotically equal to the commonly used 'approximate' maximum likelihood estimate described in the paper. For Gaussian processes, the estimates obtained by the proposed procedures are asymptotically efficient.     

A MIXED INTEGER LINEAR PROGRAMMING-BASED TECHNIQUE FOR THE ESTIMATION OF MULTIPLE GROSS ERRORS IN PROCESS MEASUREMENTS

This paper presents a new strategy for detecting, identifying, and estimating gross errors (measurement biases and leaks) in linear steady state processes. The MILP-based gross error detection and identification model is constructed aiming at identifying the minimum number of gross errors and their sizes. One significant advantage of the method is that the detection, identification, and estimation of gross errors can be performed simultaneously without using any test statistics.     

A MIXED INTEGER LINEAR PROGRAMMING-BASED TECHNIQUE FOR THE ESTIMATION OF MULTIPLE GROSS ERRORS IN PROCESS MEASUREMENTS

This paper presents a new strategy for detecting, identifying, and estimating gross errors (measurement biases and leaks) in linear steady state processes. The MILP-based gross error detection and identification model is constructed aiming at identifying the minimum number of gross errors and their sizes. One significant advantage of the method is that the detection, identification, and estimation of gross errors can be performed simultaneously without using any test statistics.     

ESTIMATION OF THE COEFFICIENTS OF A MULTIVARIATE LINEAR FILTER USING THE INNOVATIONS ALGORITHM

It is shown under mild conditions that the estimators of the coefficient matrices obtained by applying the innovations algorithm to the sample covariances of observations of the multivariate linear time series X _t = ∑^∞ _{j =0}ψ _i Z _t , t = 0, ±1, ±2, . . ., are consistent. The asymptotic distribution of the estimators is found to have a very simple form which generalizes the corresponding univariate result of Brockwell and Davis (Simple consistent estimation of the coefficients of a linear filter. In Stochastic Processes and Their Applications . Amsterdam: North- Holland, pp. 47--59). The asymptotic distribution of the corresponding estimator of the spectral density matrix is also derived. Some simulation results are presented to illustrate the small-sample behaviour of the estimators.     

LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES

Abstract. This paper considers a mean shift with an unknown shift point in a linear process and estimates the unknown shift point (change point) by the method of least squares. Pre-shift and post-shift means are estimated concurrently with the change point. The consistency and the rate of convergence for the estimated change point are established. The asymptotic distribution for the change point estimator is obtained when the magnitude of shift is small. It is shown that serial correlation affects the variance of the change point estimator via the sum of the coefficients of the linear process. When the underlying process is autoregressive moving average, a mean shift causes overestimation of its order. A simple procedure is suggested to mitigate the bias in order estimation.     

ESTIMATION OF RANDOM COEFFICIENT AUTOREGRESSIVE PROCESS: AN EMPIRICAL BAYES APPROACH

Abstract. The problem of estimating panel autoregressive time series is considered. The autoregressive parameters vary over independent realizations from an unknown distribution. An empirical Bayes procedure is suggested to estimate the parameters using information from all realizations.     

流加式聚合反应生产过程的动态模型及其参数估计

流加式聚合反应生产过程相当复杂,其模型化同时涉及聚合反应动力学、传热、相变原理以及热量、质量动态平衡定律等。本文为一类流加式聚合反应生产过程建立了动态数学模型,并基于某化工厂聚醚釜的实际运行数据估计了其中的各种参数。从而为开发此类过程的控制和优化方案提供了基础。     

ON THE SELECTION OF RANDOM SAMPLING SCHEMES FOR THE SPECTRAL ESTIMATION OF CONTINUOUS TIME PROCESSES

Abstract. Let X={X(t), -∝<t<∝} be a continuous time stationary process with spectral density φ_x(Λ) and {φ_k} be a stationary point process independent of X. The problem of selecting the sampling point process {τ_k} for the estimation of φ_x(Λ) based on the discrete time observations {X(τ_k), τ_k} is considered. Sufficient conditions are established for the admittability of a broad class of delayed renewal point processes. Examples are given for delayed renewal point processes {τ_k} which have a mixture of Gamma densities for their inter-arrival times. Guidelines are given for the selection of specific point processes in the estimation of broadband and narrowband spectral density functions.     

国外LLDPE树脂现状及发展预测

对近10年来国外部分地区和国家的线性低密度聚乙烯(LLDPE)的生产能力、产量、消费量、产品用途分配、进出口及价格情况进行了详细的综述和分析,同时对国外LLDPE的发展趋势作了预测。     

GENERALIZED SEASONAL ARIMA PROCESSES: REGULARITY/SINGULARITY CRITERIA AND LINEAR PREDICTION

Abstract. Criteria for any generalized seasonal ARIMA model to be a regular or to be a singular process are given and a new basic form of predictors for ARIMA processes is obtained, that can be computed in a simple way.     

A LIMITING PROPERTY OF SAMPLE AUTOCOVARIANCES OF PERIODICALLY CORRELATED PROCESSES WITH APPLICATION TO PERIOD DETERMINATION

Abstract. It is shown that the sample autocovariance of a periodically correlated process converges to a limit which reveals the same periodicity as the process. A theorem is proved relating to the rate of almost sure convergence, which is uniform in the lag up to some orders of observation length. Based on the limiting property, a strongly consistent estimate of hidden period is proposed.     

THE RECURSIVE PROPERTY OF THE INVERSE OF THE COVARIANCE MATRIX OF A MOVING-AVERAGE PROCESS OF GENERAL ORDER

Abstract. The inverse of the covariance matrix of a moving-average process of general order is considered. A recursive relationship between the inverses for any two consecutive orders has been established. Illustrative situations are derived and exact expressions are discussed.     

ON THE SPECTRAL DENSITY MATRIX OF A PERIODIC ARMA PROCESS

Abstract. After reviewing the spectral representation theorems for periodic stationary process, we derive a parametric formula for the spectral density of a periodic ARMA process via a new approach. The equivalence with the existing approach is shown.     

THE ZERO-CROSSING RATE OF AUTOREGRESSIVE PROCESSES AND ITS LINK TO UNIT ROOTS

Abstract. The asymptotic zero-crossing rate (ZCR) of the general second-order autoregressive process is investigated. When the associated characteristic polynomial has a unit root e ^iθ (0 ≤θ≤π), the ZCR converges in mean square to θ/π and the rate of convergence is very fast regardless of the noise level.     

INVERSE AUTOCOVARIANCES AND A MEASURE OF LINEAR DETERMINISM FOR A STATIONARY PROCESS

Abstract. The inverse autocorrelations and autocovariances of a stationary stochastic process are generally used in the identification of ARMA models and linear systems, but they are also useful for studying linear relations inside the process as a whole.
Using inverse autocovariances, for any stationary process an 'inverse process' may be defined which may be considered a minimum variance linear filter, and turns out to be the best linear two-sided interpolator for one unknown value.
Basing on these results an index of linear determinism is introduced to measure to what degree a stationary process satisfies a linear deterministic constraint. The behaviour of the index for ARMA processes is finally examined.     

生物降解塑料试验评价方法的进展

简介了活性污泥、土壤分解和特定酶、微生物分解等三类生物降解塑料的试验评价方法,以及日、美有关试验评价工作的进展,特别是美国ASTM的有关标准制订工作概况.另外,本文也简单综述了聚乙烯、乙烯基聚合物、聚酯、聚醚、聚氨酯、聚酰胺等聚合物的生物降解性及其影响因素及机理.     

预氧化过程中PAN共聚纤维密度与结构关系的研究

采用连续实验装置与工艺,借助密度、X射线衍射、红外光谱、元素分析等技术,研究了聚丙烯腈共聚纤维在连续预氧化过程中密度与结构之间的关系及有关反应过程与影响因素.研究结果表明,预氧化过程中 PAN 共聚纤维密度的变化不仅可反映出纤维结构上的各种化学和物理变化,亦可以作为一种工业生产的控制指标.     

密度组成及磁场强度对煤比磁化率影响的研究

不同密度级煤比磁化率的差异是煤磁选的依据,用Gouy磁天平对不同密度级煤比磁化率进行测定,煤比磁化率随着密度的减小而减小,小于1.5 g/cm3密度级的煤显逆磁性;低密度级煤比磁化率随着磁场强度的增加而减小,逆磁性增加,而高密度级煤比磁化率随着磁场强度增加顺磁性减弱.根据所得函数式,表明存在一最佳磁场强度使低、高密度级煤的磁性差异最大.相比较而言,密度对煤磁化率的影响更大.     

CONTINUUM MECHANICS APPLIED TO A VERY THIN LIQUID FILM: ESTIMATION OF SURFACE TENSION FOR THE n-ALKANES

This analysis demonstrates that, at least in some cases, continuum mechanics can be successfully applied in problems involving very thin films, so long as proper recognition is given to long-range intermolecular forces and to the finite size of molecules. In this particular case, the integral mechanical energy balance is used to analyze a simple thought experiment in which a thin liquid film is slowly stretched. The result is an expression for surface tension as a function of the Hamaker constant describing liquid-liquid, long-range intermolecular forces, the molecular weight, and the liquid density, which is in good agreement with previous experimental measurements for n-alkanes.     

ESTIMATION OF THE MULTIVARIATE AUTOREGRESSIVE MOVING AVERAGE HAVING PARAMETER RESTRICTIONS AND AN APPLICATION TO ROTATIONAL SAMPLING

Abstract. The vector autoregressive moving average model with nonlinear parametric restrictions is considered. A simple and easy-to-compute Newton-Raphson estimator is proposed that approximates the restricted maximum likelihood estimator which takes full advantage of the information contained in the restrictions. In the case when there are no parametric restrictions, our Newton-Raphson estimator is equivalent to the estimator proposed by Reinsel et al. (Maximum likelihood estimators in the multivariate autoregressive moving-average model from a generalized least squares view point. J. Time Ser. Anal. 13 (1992), 133–45). The Newton-Raphson estimation procedure also extends to the vector ARMAX model. Application of our Newton-Raphson estimation method in rotational sampling problems is discussed. Simulation results are presented for two different restricted models to illustrate the estimation procedure and compare its performance with that of two alternative procedures that ignore the parametric restrictions.