苏雪林文学批评之比较方法的运用

在苏雪林的文学批评中，比较手法的运用是极为显著且常见的。中国古典文学深厚的积淀，西方文学文化的深刻熏陶，使其比较之法不仅仅涉及到同时期、同流派作家之间的平行比较，更有以古典文学为借鉴的古今比较，及以西方文学为参照的中西比较。这种多层次、多方面的比较，使中国现代文学在苏雪林的评论中处于一个广阔而又立体的环境中，这一方面突显了苏雪林的敏锐观察力，同时也折射出了中国现代文学在中西纵横交错中的独特魅力。     

Alternative estimators in logistic regression when the data are collinear

Logistic regression using conditional maximum likelihood estimation has recently gained widespread use. Many of the applications of logistic regression have been in situations in which the independent variables are collinear. It is shown that collinearity among the independent variables seriously effects the conditional maximum likelihood estimator in that the variance of this estimator is inflated in much the same way that collinearity inflates the variance of the least squares estimator in multiple regression. Drawing on the similarities between multiple and logistic regression several alternative estimators, which reduce the effect of the collinearity and are easy to obtain in practice, are suggested and compared in a simulation study.     

Testing for a change point in a sequence of exponential random variables with repeated values

Two test statistics are proposed for the change-point problem with repeated values when the data follow an exponential distribution. The properties of these two statistics have been studied and their asymptotic distributions under the alternative have been derived. The powers of the two test statistics are compared. Real-data examples are presented to illustrate the application of these tests.     

Uniform Test for Predictive Regression With AR Errors

Testing predictability is of importance in economics and finance. Based on a predictive regression model with independent and identically distributed errors, some uniform tests have been proposed in the literature without distinguishing whether the predicting variable is stationary or nearly integrated. In this article, we extend the empirical likelihood methods of Zhu, Cai, and Peng with independent errors to the case of an AR error process. Again, the proposed new tests do not need to know whether the predicting variable is stationary or nearly integrated, and whether it has a finite variance or an infinite variance. A simulation study shows the new methodologies perform well in finite sample.     

Evidential inference for diffusion-type processes

This article analyses diffusion-type processes from a new point-of-view. Consider two statistical hypotheses on a diffusion process. We do not use a classical test to reject or accept one hypothesis using the Neyman–Pearson procedure and do not involve Bayesian approach. As an alternative, we propose using a likelihood paradigm to characterizing the statistical evidence in support of these hypotheses. The method is based on evidential inference introduced and described by Royall [Royall R. Statistical evidence: a likelihood paradigm. London: Chapman and Hall; 1997]. In this paper, we extend the theory of Royall to the case when data are observations from a diffusion-type process instead of iid observations. The empirical distribution of likelihood ratio is used to formulate the probability of strong, misleading and weak evidences. Since the strength of evidence can be affected by the sampling characteristics, we present a simulation study that demonstrates these effects. Also we try to control misleading evidence and reduce them by adjusting these characteristics. As an illustration, we apply the method to the Microsoft stock prices.     

Time series models with asymmetric Laplace innovations

We propose autoregressive moving average (ARMA) and generalized autoregressive conditional heteroscedastic (GARCH) models driven by asymmetric Laplace (AL) noise. The AL distribution plays, in the geometric-stable class, the analogous role played by the normal in the alpha-stable class, and has shown promise in the modelling of certain types of financial and engineering data. In the case of an ARMA model we derive the marginal distribution of the process, as well as its bivariate distribution when separated by a finite number of lags. The calculation of exact confidence bands for minimum mean-squared error linear predictors is shown to be straightforward. Conditional maximum likelihood-based inference is advocated, and corresponding asymptotic results are discussed. The models are particularly suited for processes that are skewed, peaked, and leptokurtic, but which appear to have some higher order moments. A case study of a fund of real estate returns reveals that AL noise models tend to deliver a superior fit with substantially less parameters than normal noise counterparts, and provide both a competitive fit and a greater degree of numerical stability with respect to other skewed distributions.     

A note on bias reduction of maximum likelihood estimates for the scalar skew t distribution

The skew t distribution is a flexible parametric family to fit data, because it includes parameters that let us regulate skewness and kurtosis. A problem with this distribution is that, for moderate sample sizes, the maximum likelihood estimator of the shape parameter is infinite with positive probability. In order to try to solve this problem, Sartori (2006) has proposed using a modified score function as an estimating equation for the shape parameter. In this note we prove that the resulting modified maximum likelihood estimator is always finite, considering the degrees of freedom as known and greater than or equal to 2.     

“赔礼道歉”的异化与回归

我国《侵权责任法》延续了《民法通则》的规定,将赔礼道歉作为侵权责任承担方式之一种。从赔礼道歉责任承担方式在我国的产生来看,其有一定的历史时代原因;但在现代法的背景之下,该种责任承担方式不仅在理论上争议颇多,而且造成了司法实践中问题重重,其作为一种责任承担方式的合理性值得怀疑,将其从法律责任还原为道德责任实属必要。     

BL-GARCH models with elliptical distributed innovations

In this work, we discuss the class of bilinear GARCH (BL-GARCH) models that are capable of capturing simultaneously two key properties of non-linear time series: volatility clustering and leverage effects. It has often been observed that the marginal distributions of such time series have heavy tails; thus we examine the BL-GARCH model in a general setting under some non-normal distributions. We investigate some probabilistic properties of this model and we conduct a Monte Carlo experiment to evaluate the small-sample performance of the maximum likelihood estimation (MLE) methodology for various models. Finally, within-sample estimation properties were studied using S&P 500 daily returns, when the features of interest manifest as volatility clustering and leverage effects. The main results suggest that the Student-t BL-GARCH seems highly appropriate to describe the S&P 500 daily returns.     

Responding to child deaths: the work of Australia's Victorian Child Death Review Committee

The Victorian Child Death Review Committee (VCDRC) in Australia is a multidisciplinary Ministerial Advisory Committee established to review the deaths of children either currently child protection clients or known to the statutory child protection system. The Committee provides advice about each child death as well as insights into what are the surrounding patterns and issues. Key to this role is examining the contribution of the service sectors to the protection of children and the routine practices that are in place to respond to children and vulnerability. This paper provides a snapshot of the cases referred to the VCDRC and the key messages for practice drawn from them. What emerges is that often the threshold for when statutory child protection services must be involved in child and family matters can be ambiguous and that agreement about intervention, the level and nature of need or risk, and when cumulative harm and neglect require statutory responses are not always shared between agencies. It is clear that the lack of common frameworks about what constitutes child protection intervention challenges services. It is recommended that there be and used agreed definitions and frameworks to ensure shared understandings and collaborative responses across the service and legal systems.