Slack-variable models versus Scheffé's mixture models

Slack-variable models are compared against Scheffé's polynomial model for mixture experiments. The notion of model equivalence and the use of various diagnostic measures provide effective tools in making such comparisons, particularly when the experimental region is highly constrained. It is demonstrated that the choice of the best fitting model, through variable selection, depends on which mixture component is selected as a slack variable, and on the size of the fitted model. In addition, the equivalence of two well-known representations of a complete mixture model is shown to be valid. Two numerical examples are presented.     

时间序列的新息预报

根据实际问题，针对有限个数据ｗｋ，ｗｋ－１，…，ｗ１，给出了Ｗｋ＋ｌ的严格的线性最小方差预报和实现这种预报的适时递推公式和计算方法，并与平稳预报进行比较，得到两者有渐近相等的一步预报误差方差。     

Change-of-variance problem for linear processes with long memory

In this paper we investigate the asymptotic properties of the test statistics for detecting change-points in the variance of infinite moving average sequences with long memory. This research is partly supported by NSFC Grants and SRF for ROCS, SEM.     

Self-weighted least absolute deviation estimation for infinite variance autoregressive models

Summary.  How to undertake statistical inference for infinite variance autoregressive models has been a long-standing open problem. To solve this problem, we propose a self-weighted least absolute deviation estimator and show that this estimator is asymptotically normal if the density of errors and its derivative are uniformly bounded. Furthermore, a Wald test statistic is developed for the linear restriction on the parameters, and it is shown to have non-trivial local power. Simulation experiments are carried out to assess the performance of the theory and method in finite samples and a real data example is given. The results are entirely different from other published results and should provide new insights for future research on heavy-tailed time series.     

Conservative prior distributions for variance parameters in hierarchical models

Bayesian hierarchical models typically involve specifying prior distributions for one or more variance components. This is rather removed from the observed data, so specification based on expert knowledge can be difficult. While there are suggestions for “default” priors in the literature, often a conditionally conjugate inverse‐gamma specification is used, despite documented drawbacks of this choice. The authors suggest “conservative” prior distributions for variance components, which deliberately give more weight to smaller values. These are appropriate for investigators who are skeptical about the presence of variability in the second‐stage parameters (random effects) and want to particularly guard against inferring more structure than is really present. The suggested priors readily adapt to various hierarchical modelling settings, such as fitting smooth curves, modelling spatial variation and combining data from multiple sites.     

REMARKS ON OPTIMAL INFERENCE FOR MARKOV BRANCHING PROCESSES: A SEQUENTIAL APPROACH

Use of a suitable stopping rule yields exact uniformly most powerful tests and minimum variance unbiased estimators of various parameters of a Markov branching model with or without immigration. The population model discussed includes the pure birth, simple epidemic, immigration-death, M/M/ 1 queue, linear birth-death and a branching diffusion process, among others, as special cases.     

Hardiness and the relationship between stressors and outcomes

Using a sample of 468 participants, from two organizations, this study examined direct and moderating relationships between hardiness (a composite of challenge, control, and commitment), life and work stressors, and a variety of health-related outcomes. The results indicated that hardiness did not moderate the relationship between stressors and outcomes as reported by others (e.g. Kobasa 1982a). However, hardiness did have significant direct effects on emotional and psychological factors thought to be related to personal well-being and work performance. Hardy individuals reported higher levels of job satisfaction and fewer tensions at work dun did the less hardy. In general, hardy individuals experienced a higher quality of life and a more positive affect while being more energized and less negative about life. Hardy individuals also reported fewer somatic complaints and tended to be less depressed and anxious than individuals low in hardiness. In addition, hardiness was negatively related to all four measures of life and work stress implying that hardiness may not be independent of life demands.     

M-Estimates of regression when the scale is unknown and the error distribution is possibly asymmetric: A minimax result

Huber (1964) found the minimax-variance M-estimate of location under the assumption that the scale parameter is known; Li and Zamar (1991) extended this result to the case when the scale is unknown. We consider the robust estimation of the regression coefficients (β₁,…,β_p) when the scale and the intercept parameters are unknown. The minimax-variance estimates of (β₁,…,β_p) with respect to the trace of their asymptotic covariance matrix are derived. The maximum is taken over ?-contamination neighbourhoods of a central regression model with Gaussian errors (asymmetric contamination is allowed), and the minimum is taken over a large class of generalized M-estimates of regression of the Mallow type. The optimal choice of estimates for the nuisance parameters (scale and intercept) is also considered.     

Rank-order tests for the parallelism of several regression surfaces

For testing the hypothesis that several (s?2) linear regression surfaces X_ki=α_k+β_kc_ki+Z_ki (k=1,…,s) are parallel to one another, i.e., β₁=?=β_s, a class of rank-order tests are considered. The tests are shown to be asymptotically distribution-free, and their asymptotic efficiency relative to the general likelihood ratio test is derived. Asymptotic optimality in the sense of Wald is also discussed.     

中美棉花期货价格引导和均衡关系的实证分析

对中国棉花期货上市至实证结束期间796个价格数据,运用Eviews软件的协整分析、Granger因果检验、误差修正模型和方差分解法,实证检验了中国和美国棉花期货价格之间的关系,结果表明:中美棉花期货价格之间的协整关系成立,两者具有显著的长期稳定关系;中美棉花期货价格间存在显著的相互引导关系;短期内美国棉花期货价格变动是中国棉花期货价格变动Granger意义上的原因;中国期货价格虽受到美国棉花期货价格的影响,但具有较强的独立性。