马尔可夫协整回归模型的动态滤波估计

本文提出动态滤波估计方法估计马尔可夫协整回归模型的参数.利用领先和滞后方法构造辅助的动态回归模型,以消除解释变量和误差序列间的相关性以及误差自相关性对估计结果的影响.在Hamilton滤波基础上,应用极大似然方法估计辅助模型的参数.模拟计算结果表明动态滤波估计方法能降低误差序列相关性造成的估计偏差.对1990年1月至2011年10月的中国进出口贸易数据,利用所提方法建立了马尔可夫协整回归模型.     

On pseudo maximum likelihood estimation for multivariate time series models with conditional heteroskedasticity

We consider a general multivariate conditional heteroskedastic model under a conditional distribution that is not necessarily normal. This model contains autoregressive conditional heteroskedastic (ARCH) models as a special class. We use the pseudo maximum likelihood estimation method and derive a new estimator of the asymptotic variance matrix for the pseudo maximum likelihood estimator. We also study four special cases in this class, which are conditional heteroskedastic autoregressive moving-average models, regression models with ARCH errors, models with constant conditional correlations, and ARCH in mean models.     

Testing for jumps in the stochastic volatility models

This paper proposes the Lagrange multiplier (LM) test, or the score test, for jumps in the stochastic volatility (SV) model in the cases where the innovation term follows the normal and Student t-distributions. The tested null hypothesis is that the jump density has zero variance, which is expressed by Dirac’s delta function. It is shown that the unknown jump probability, which is an unidentified parameter under the null hypothesis, is cancelled out in the LM test statistic, and hence this test is free from the estimation problem of unidentified parameters, which is known as the Davies problem [R.B. Davies, Hypothesis testing when a nuisance parameter is present only under the alternative, Biometrika 64 (1977) 247–254]. Monte Carlo experiments show that the null distribution of the LM test statistic can be approximated by the normal distribution with sufficient accuracy.     

Restricted regression estimation in measurement error models

The problem of consistent estimation of the regression coefficients when some prior information about the regression coefficients is available is considered. Such prior information is expressed in the form of exact linear restrictions. The knowledge of covariance matrix of measurement errors that is associated with explanatory variables is used to construct the consistent estimators. Some consistent estimators are suggested which satisfy the exact linear restrictions also. Their asymptotic properties are derived and analytically analyzed under a multivariate ultrastructural model with not necessarily normally distributed measurement errors. The finite sample properties of the estimators are studied through a Monte-Carlo simulation experiment.     

Semiparametrically weighted robust estimation of regression models

A class of two-step robust regression estimators that achieve a high relative efficiency for data from light-tailed, heavy-tailed, and contaminated distributions irrespective of the sample size is proposed and studied. In particular, the least weighted squares (LWS) estimator is combined with data-adaptive weights, which are determined from the empirical distribution or quantile functions of regression residuals obtained from an initial robust fit. Just like many existing two-step robust methods, the LWS estimator with the proposed weights preserves robust properties of the initial robust estimate. However, contrary to the existing methods and despite the data-dependent weights, the first-order asymptotic behavior of LWS is fully independent of the initial estimate under mild conditions. Moreover, the proposed estimation method is asymptotically efficient if errors are normally distributed. A simulation study documents these theoretical properties in finite samples; in particular, the relative efficiency of LWS with the proposed weighting schemes can reach 85%-100% in samples of several tens of observations under various distributional models.     

Consistent estimation in regression models for the drift function in some continuous time models

A regression-based consistent estimation method for the drift function in some continuous time models is suggested, and its limiting distribution is derived. The accuracy of the new estimation method is examined via some finite sample Monte Carlo simulation studies. The proposed approach is employed to estimate the drift function for the U.S. Treasury Bill yields data, assuming the appropriateness of the model under consideration for it. Our approach offers an explanation for versatile conclusions on the shape of drift function in the existing literature.     

Local polynomial estimation in partial linear regression models under dependence

A regression model whose regression function is the sum of a linear and a nonparametric component is presented. The design is random and the response and explanatory variables satisfy mixing conditions. A new local polynomial type estimator for the nonparametric component of the model is proposed and its asymptotic normality is obtained. Specifically, this estimator works on a prewhitening transformation of the dependent variable, and the results show that it is asymptotically more efficient than the conventional estimator (which works on the original dependent variable) when the errors of the model are autocorrelated. A simulation study and an application to a real data set give promising results.     

The role of “hierarchy” in the design of fuzzy logiccontrollers

This paper investigates the role of hierarchy in the systematic approach to the design of fuzzy logic controllers (FLC's). The key concept here is that the implementation of fuzzy engines at higher levels of the control hierarchy (where more reasoning is involved) yields more versatile fuzzy controllers with generally fewer control rules. At the same time, the structured nature of a hierarchical approach considerably simplifies the design procedure.     

C22 BxNy(x+y=2)全部异构体和分子离子芳香性的研究

用拓扑共振能(TRE)和百分拓扑共振能(%TRE)方法,研究从富勒烯C24(D6)产生异质富勒烯C22N2,C22B2和C22BN的所有异构体,研究阳离子和阴离子的芳香性.分析C22BxNy中杂原子取代位置和稳定性之间的关系.结果,中性状态和阳离子状态中,各异构体的TRE都为负数具有反芳香性.但它们的高价阴离子的TRE都为正数则有芳香性.中性状态中,稳定性顺序为:C22N2(1-19)>C22BN(39-64)>C24>C22B2(20-38).形成闭壳层结构时稳定性顺序为:C22B8-2(20-38>C6-24>C22BN6-(39-64)>C22N4-2(1-19).无论在中性状态还是闭壳层结构,当N原子取代C2类碳原子,B原子取代C1类碳原子时最稳定.理论上,预测C22BxNy的高价阴离子有合成的可能性.     

Meta-heuristic algorithms for parameter estimation of semi-parametric linear regression models

Consider the semi-parametric linear regression model Y=β^′X+ε, where ε has an unknown distribution F₀. The semi-parametric MLE of β under this set-up is called the generalized semi-parametric MLE(GSMLE). Although the GSML estimation of the linear regression model is statistically appealing, it has never been attempted due to difficulties with obtaining the GSML estimates of β and F until recent work on linear regression for complete data and for right-censored data by Yu and Wong [2003a. Asymptotic properties of the generalized semi-parametric MLE in linear regression. Statistica Sinica 13, 311-326; 2003b. Semi-parametric MLE in simple linear regression analysis with interval-censored data. Commun. Statist.—Simulation Comput. 32, 147-164; 2003c. The semi-parametric MLE in linear regression with right censored data. J. Statist. Comput. Simul. 73, 833-848]. However, after obtaining all candidates, their algorithm simply does an exhaustive search to find the GSML estimators. In this paper, it is shown that Yu and Wong's algorithm leads to the so-called dimension disaster. Based on their idea, a simulated annealing algorithm for finding semi-parametric MLE is proposed along with techniques to reduce computations. Experimental results show that the new algorithm runs much faster for multiple linear regression models while keeping the nice features of Yu and Wong's original one.     

Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models

This paper studies the linear dynamic errors-in-variables problem for filtered white noise excitations. First, a frequency domain Gaussian maximum likelihood (ML) estimator is constructed that can handle discrete-time as well as continuous-time models on (a) part(s) of the unit circle or imaginary axis. Next, the ML estimates are calculated via a computationally simple and numerically stable Gauss-Newton minimization scheme. Finally, the Cramér-Rao lower bound is derived.     

Testing for jumps in the EGARCH process

This paper considers testing for jumps in the exponential GARCH (EGARCH) models with Gaussian and Student-t innovations. The Wald and log likelihood ratio tests contain a nuisance parameter unidentified under the null hypothesis of no jumps, and hence are unavailable for this problem, because jump probability and variance of jumps in the test statistic cannot be estimated under the null hypothesis of no jumps. It is shown that the nuisance parameter is cancelled out in the Lagrange multiplier (LM) test statistic, and hence that the test is nuisance parameter-free. The one-sided test is also proposed using the nonnegative constraint on jump variance. The actual size and power of the tests are examined in a Monte Carlo experiment. The test is applied to daily returns of S&P 500 as an illustrative example.     

Visual comparison of software cost estimation models by regression error characteristic analysis

The well-balanced management of a software project is a critical task accomplished at the early stages of the development process. Due to this requirement, a wide variety of prediction methods has been introduced in order to identify the best strategy for software cost estimation. The selection of the best technique is usually based on measures of error whereas in more recent studies researchers use formal statistical procedures. The former approach can lead to unstable and erroneous results due to the existence of outlying points whereas the latter cannot be easily presented to non-experts and has to be carried out by an expert with statistical background. In this paper, we introduce the regression error characteristic (REC) analysis, a powerful visualization tool with interesting geometrical properties, in order to validate and compare different prediction models easily, by a simple inspection of a graph. Moreover, we propose a formal framework covering different aspects of the estimation process such as the calibration of the prediction methodology, the identification of factors that affect the error, the investigation of errors on certain ranges of the actual cost and the examination of the distribution of the cost for certain errors. Application of REC analysis to the ISBSG10 dataset for comparing estimation by analogy and linear regression illustrates the benefits and the significant information obtained.     

The iteration method of data censoring in the regression estimation problem

A robust analog of the Nadaraya-Watson regression estimate is considered. A solution is obtained in the class of censor algorithms. A criterion and iteration procedure for determining a censored sample are proposed. The criterion is based on the analysis of residuals (errors) of estimation.     

基于粒子群算法的Logistic回归模型参数估计

针对Logistic回归模型中的参数估计计算复杂难题,提出一种基于粒子群优化算法（PSO）的估计方法。以最大似然准则作为粒子群优化算法的适应度函数,建立了Logistic回归模型中的参数估算模型。数值仿真分析表明,粒子群优化算法可以更精确地计算出相关参数。     

Alternative approaches to implementing Lagrange multiplier tests for serial correlation in dynamic regression models

An approximate F-form of the Lagrange multiplier (LM) test for serial correlation in dynamic regression models is compared with three bootstrap tests. In one bootstrap procedure, residuals from restricted estimation under the null hypothesis are resampled. The other two bootstrap tests use residuals from unrestricted estimation under an alternative hypothesis. A fixed autocorrelation alternative is assumed in one of the two unrestricted bootstrap tests and the other is based upon a Pitman-type sequence of local alternatives. Monte Carlo experiments are used to estimate rejection probabilities under the null hypothesis and in the presence of serial correlation.     

Testing the Power of a Generalization of the KPSS-Tests against Fractionally Integrated Hypotheses

We analyse in this article the size and the power properties of differentgeneralizations of the KPSS-tests proposed by Hobjin et al. (1998) for testingthe null hypothesis of stationarity in univariate time series when thealternatives are of a fractional form. We show that the test based on the useof the Quadratic Spectral kernel along with an automatic bandwidth selectionprocedure produces the best results and thus, it might be employed for testingI(0) against I(d>0) stationary or nonstationary processes. An empiricalapplication, showing the performance of the tests in finite samples is alsocarried out at the end of the article.     

The impact of structural breaks on the integration of the ASEAN-5 stock markets

This paper examines the ASEAN-5 countries and explores the impact of structural breaks on the level of financial integration in that region. An extended cointegration procedure allowing for three types of structural break, is employed and compared with the standard Johansen procedure, for daily and weekly returns. The empirical results suggest a higher level of integration within the ASEAN-5 markets than previously found, suggesting that financial risk reduction benefits from diversifying investments across the region are less than previously thought. Further, Singapore and Thailand are the main long-term drivers in the region; Malaysia and Indonesia are more short-term drivers. Structural breaks are found to correspond with the Asian financial crisis in 1997/98 and a possible Y2K effect in late 1999. Results are verified using another structural break model and method, where break dates are treated as known.     

The use of “bug” in computing

There has been much speculation concerning the early use of the word “bug” in the language of computer science, technology, and practice. The purpose of the article is to indicate what may be the earliest application of “bug” in the context of computers. When the IBM ASCC/Harvard Mark I was installed at Harvard University, Robert V.D. Campbell was in charge of the operation of the machine. Bob Campbell supervised the testing and first runs of the machine and remained in charge of the machine and its operation until the spring of 1944. Campbell kept a detailed log book, recording almost every aspect of the operation of the new machine, including the preparation of the first programs and the various kinds of difficulties that arose. On April 17 1944, Campbell recorded an entry in which reference was made to “bugs” in the ASCC/Mark 1. This is thought to be the first mention of the word “bug” in relation to a computer