On a superiority problem in misspecified restricted linear models

Razzaghi (1987) conjectures that a wrong choice of covariance matrix in a restricted linear model results in loss of efficiency, This conjecture is proved to be correct.     

Constructing 1-rotational NRDFs through an optimization approach: new (46,9,8), (51,10,9) and (55,9,8)-NRBDs

In this paper we formulate the problem of constructing 1-rotational near resolvable difference families as a combinatorial optimization problem where a global optimum corresponds to a desired difference family. Then, we develop an algorithm based on scatter search in conjunction with a tabu search to construct many of these difference families. In particular, we construct three new near resolvable difference families which lead to an equal number of new 1-rotational near resolvable block designs with parameters: (46,9,8), (51,10,9) and (55,9,8). Our results indicate that this conjunction outperforms both scatter search and tabu search.     

耐温耐盐聚合物堵剂的制备及性能研究

针对高温高矿化度地质条件特点，合成了对苯乙烯磺酸钠–2–丙烯酰胺基–2–甲基丙磺酸–膨润土聚合物堵剂。采用不同浓度盐溶液、使用温度及时间评价其耐盐耐温性能，优化了携带液体系，采用岩芯模拟实验考察堵剂封堵效果及耐冲刷性能。结果表明：该堵剂在80130 ℃恒温放置60 d 后树脂的吸水率和强度基本保持不变，树脂耐温性能良好；在质量分数30% 的模拟盐水溶液中吸水率仍可达12.00 g
g..1，树脂的耐盐性能良好；树脂在含水40% 的乳化油中3 h 不膨胀；岩芯实验测定聚合物堵剂在高渗和中渗通道中封堵率达到99.96% 和96.41%，经30 PV 水长期冲刷封堵率仍可达95.12% 和94.43%。     

关于加权广义逆的三个矩阵乘积的不变性

利用矩阵D-AXC的最大最小秩,给出了矩阵AXC的乘积、秩以及值域的不变性,其中X为矩阵B的各种加权广义逆.     

Computational Examples of a New Method for Distribution Selection in the Pearson System

A considerable problem in statistics and risk management is finding distributions that capture the complex behaviour exhibited by financial data. The importance of higher order moments in decision making has been well recognized and there is increasing interest in modelling with distributions that are able to account for these effects. The Pearson system can be used to model a wide scale of distributions with various skewness and kurtosis. This paper provides computational examples of a new easily implemented method for selecting probability density functions from the Pearson family of distributions. We apply this method to daily, monthly, and annual series using a range of data from commodity markets to macroeconomic variables.     

中国市场条件下大单交易价格行为的不对称性研究

在中国证券市场选取大盘环境不同的时段,利用配对技术消除样本系统误差,对大单买卖价格冲击不对称性及该不对称与市场环境之间的关系进行了实证分析。研究表明:中国证券市场的大单买卖价格冲击存在显著不对称性,且该不对称性与市场环境相关。当大盘上涨时,买入订单的价格冲击均比卖出订单大,当大盘下跌时,卖出订单的价格冲击多数比买入订单要大。     

E-optimal design in irregular BIBD settings

When the necessary conditions for a BIBD are satisfied, but no BIBD exists, there is no simple answer for the optimal design problem. This paper identifies the E-optimal information matrices for any such irregular BIBD setting when the number of treatments is no larger than 100. A- and D-optimal designs are typically not E-optimal. An E-optimal design for 15 treatments in 21 blocks of size 5 is found.     

CO-tucker: a new method for the simultaneous analysis of a sequence of paired tables

Relationships between species and their environment are a key component to understand ecological communities. Usually, this kind of data are repeated over time or space for communities and their environment, which leads to a sequence of pairs of ecological tables, i.e. multi-way matrices. This work proposes a new method which is a combined approach of STATICO and Tucker3 techniques and deals to the problem of describing not only the stable part of the dynamics of structure–function relationships between communities and their environment (in different locations and/or at different times), but also the interactions and changes associated with the ecosystems’ dynamics. At the same time, emphasis is given to the comparison with the STATICO method on the same (real) data set, where advantages and drawbacks are explored and discussed. Thus, this study produces a general methodological framework and develops a new technique to facilitate the use of these practices by researchers. Furthermore, from this first approach with estuarine environmental data one of the major advantages of modeling ecological data sets with the CO-TUCKER model is the gain in interpretability.     

Accuracy of variational estimates for random graph mixture models

Variational and variational Bayes techniques are popular approaches for statistical inference of complex models but their theoretical properties are still not well known. Because of both unobserved variables and intricate dependency structures, mixture models for random graphs constitute a good case study. We first present four different variational estimates for the parameters of these models. We then compare their accuracy through simulation studies and show that the variational Bayes estimates seem the most accurate for moderate graph size. We finally re-analyse the regulatory network of Escherichia coli with this approach.     

Γ-Optimal decision procedures for selecting the best population in randomized complete block design

In randomized complete block design, we face the problem of selecting the best population. If some partial information about the unknown parameters is available, then we wish to delermine the optimal decisin rule to select the best population.

In this paper, in the class of natural selection rules, we employ the Γ-optimal criterion to determine optimal decision rules that will minimize the maximum expected risk over the class of some partial information. Furthermore, the traditional hypothesis testing is briefly discussed from the view point of ranking and selecting.