Social security law: what does the politics of ‘conditional welfare’ mean for review and client representation?

This paper reflects on aspects of the meaning of new social security as ‘conditional welfare’ (such as welfare quarantining) and its implications for client rights, advocacy and public policy accountability. The paper considers the rising reliance on conditional welfare and related measures such as ‘linked‘, localised or place‐based welfare, and the increasing complexity of welfare discretions. The paper essentially makes the argument that it is past time to begin to debate the pros and cons for Australia of conditional welfare as it impacts on administrative law and new forms of welfare advocacy.     

Long memory in intertrade durations,counts and realized volatility of NYSE stocks

We study the persistence of intertrade durations, counts (number of transactions in equally spaced intervals of clock time), squared returns and realized volatility in 10 stocks trading on the New York Stock Exchange. A semiparametric analysis reveals the presence of long memory in all of these series, with potentially the same memory parameter. We introduce a parametric latent-variable long-memory stochastic duration (LMSD) model which is shown to better fit the data than the autoregressive conditional duration model (ACD) in a variety of ways. The empirical evidence we present here is in agreement with theoretical results on the propagation of memory from durations to counts and realized volatility presented in Deo et al. (2009).     

动态信息系统中一种基于条件熵的核属性计算方法

针对动态信息系统中新增和退出对象集的情况,在信息观下提出了一种基于条件熵的核属性计算方法。先分别讨论仅有对象集进入、仅有对象集退出以及以上两种情形同时存在下条件熵的变化机制。由条件熵变化机制,通过构造支持度矩阵和增量矩阵方式将新增或者退出的对象集一并参与比较计算,快速求得条件熵,进而获得核属性。最后,由实例分析验证该方法的有效性。     

文学性的多元动态阐释

鉴于学界对文学性的界定十分模糊,常常因为不能合理地处理文学性各相关因素的位置及其相互关系而造成争议,为进一步奠定文学研究及文学翻译研究的基础,运用归纳与演绎的论证方法总结了形式主义及解构主义的极端视角,并在此基础上借用法国学者热拉尔·热奈特的“构成论诗学”和“条件论诗学”两大概念,分析了文学性各相关因素的性质及其在文学研究中的作用。分析认为：文学性具有多元、动态、开放的特征;在文学性的多元构成中,各个单元均在各自的范围内发挥作用,彼此相互交叉、融合、渗透,任何一个单元都不可能解释整个复杂的文学现象。     

汉语自然话语韵律组块的优选论分析

韵律是影响语音合成自然度的一个重要因素,韵律结构的预测是一个韵律组块过程。使用自然话语材料,依靠听感,对语料进行了韵律切分。通过对切分结果的考察,可以发现,韵律组块受词性及节奏等多方面因素的制约,现代音系学理论优选论可以对韵律组块问题作出解释。     

Conditional approval: discussion points from the PSI conditional approval expert group

The European Agency for the Evaluation of Medicinal Products has recently completed the consultation of a draft guidance on how to implement conditional approval. This route of application is available for orphan drugs, emergency situations and serious debilitating or life-threatening diseases. Although there has been limited experience in implementing conditional approval to date, PSI (Statisticians in the Pharmaceutical Industry) sponsored a meeting of pharmaceutical statisticians with an interest in the area to discuss potential issues. This article outlines the issues raised and resulting discussions, based on the group's interpretation of the legislation. Conditional approval seems to fit well with the accepted regulatory strategy in HIV. In oncology, conditional approval may be most likely when (a) compelling phase II data are available using accepted clinical outcomes (e.g. progression/recurrence-free survival or overall survival) and Phase III has been planned or started, or (b) when data are available using a surrogate endpoint for clinical outcome (e.g. response rate or biochemical measures) from a single-arm study in rare tumours with high response, compared with historical data. The use of interim analyses in Phase III for supporting conditional approval raises some challenging issues regarding dissemination of information, maintenance of blinding, potential introduction of bias, ethics, switching, etc.     

基于状态转移信息对FF三因子模型的改进

以1995年6月-2005年12月期间在我国沪深A股市场上市的全部股票为样本,本文实证发现,在新的样本期间,FF三因子模型不能对组合收益作出完全的解释。为了基于现代金融理论的基本观点对组合收益作出完全解释,本文利用状态转移信息对无条件的FF三因子模型进行改进,实证发现,改进后的状态转移的条件定价模型对我国股市的组合收益作出了完全解释。由此得出结论认为,在解释组合收益时,状态转移的条件定价模型是一个优于无条件FF三因子模型的模型。     

Semiparametric efficient estimation for the auxiliary outcome problem with the conditional mean model

The authors consider semiparametric efficient estimation of parameters in the conditional mean model for a simple incomplete data structure in which the outcome of interest is observed only for a random subset of subjects but covariates and surrogate (auxiliary) outcomes are observed for all. They use optimal estimating function theory to derive the semiparametric efficient score in closed form. They show that when covariates and auxiliary outcomes are discrete, a Horvitz‐Thompson type estimator with empirically estimated weights is semiparametric efficient. The authors give simulation studies validating the finite‐sample behaviour of the semiparametric efficient estimator and its asymptotic variance; they demonstrate the efficiency of the estimator in realistic settings.     

Conditions for consistent estimation in mixed-effects models for binary matched-pairs data

Parametric mixed-effects logistic models can provide effective analysis of binary matched-pairs data. Responses are assumed to follow a logistic model within pairs, with an intercept which varies across pairs according to a specified family of probability distributions G. In this paper we give necessary and sufficient conditions for consistent covariate effect estimation and present a geometric view of estimation which shows that when the assumed family of mixture distributions is rich enough, estimates of the effect of the binary covariate are typically consistent. The geometric view also shows that under the conditions for consistent estimation, the mixed-model estimator is identical to the familar conditional-likelihood estimator for matched pairs. We illustrate the findings with some examples.     

Simple and accurate inference for the mean of the gamma model

The two-parameter gamma model is widely used in reliability, environmental, medical and other areas of statistics. It has a two-dimensional sufficient statistic, and a two-dimensional parameter which can be taken to describe shape and mean. This makes it closely comparable to the normal model, but it differs substantially in that the exact distribution for the minimal sufficient statistic is not available. Some recently developed asymptotic theory is used to derive an approximation for observed levels of significance and confidence intervals for the mean parameter of the model. The approximation is as easy to apply as first-order methods, and substantially more accurate.