On estimation of population mean based on two measurements

There are many estimators for population mean: arithmetic mean, median, root mean square, geometric mean, harmonic mean, and so forth. Which one is the best? Here, we answer this question given two measurements from a uniform distribution.     

Theoretical L-moments and TL-moments using combinatorial identities and finite operators

Moments have been traditionally used to characterize a probability distribution. Recently, linear moments (L-moments) and trimmed L-moments (TL-moments) are appealing alternatives to the conventional moments. This paper focuses on the computation of theoretical L-moments and TL-moments and emphasizes the use of combinatorial identities. We are able to derive new closed-form formulas of L-moments and TL-moments for continuous probability distributions. Finally, closed-form formulas for the L-moments for the exponential distribution and the uniform distribution are also obtained.     

Nonparametric estimation of mean residual functions

Situations frequently arise in practice in which mean residual life (mrl) functions must be ordered. For example, in a clinical trial of three experiments, let e (1), e (2) and e (3) be the mrl functions, respectively, for the disease groups under the standard and experimental treatments, and for the disease-free group. The well-documented mrl functions e (1) and e (3) can be used to generate a better estimate for e (2) under the mrl restriction e (1) < or = e (2) < or = e (3). In this paper we propose nonparametric estimators of the mean residual life function where both upper and lower bounds are given. Small and large sample properties of the estimators are explored. Simulation study shows that the proposed estimators have uniformly smaller mean squared error compared to the unrestricted empirical mrl functions. The proposed estimators are illustrated using a real data set from a cancer clinical trial study.     

Exact conditional inference for two uniform populations

We discuss the nature of ancillary information in the context of the continuous uniform distribution. In the one-sample problem, the existence of sufficient statistics mitigates conditioning on the ancillary configuration. In the two-sample problem, additional ancillary information becomes available when the ratio of scale parameters is known. We give exact results for conditional inferences about the common scale parameter and for the difference in location parameters of two uniform distributions. The ancillary information affects the precision of the latter through a comparison of the sample value of the ratio of scale parameters with the known population value. A limited conditional simulation compares the Type I errors and power of these exact results with approximate results using the robust pooled t-statistic.     

含参变量广义积分一致收敛的Heine定理

从二元函数一致极限的角度出发,给出了含参变量广义积分一致收敛的Heine定理的简单证明及应用.     

中国区际刑法概念及基本体系

中国区际刑法是指,为解决中国区际刑事法律问题而确立的法律原则以及相应规范的总称。中国区际刑法这一体系,包括中国区际刑事管辖权冲突及其解决、中国区际刑事司法互助、中国区际统一刑事法律等三个范畴;三个范畴关系紧密,形成中国区际刑法的基本体系,具有一体化解决中国区际刑事法律问题的意义。     

羁縻与渗透:抗战时期国民党政权处理西北民族问题策略透视——以1937年甘肃卓尼事变为例

1937年8月,甘肃卓尼发生藏族土司杨积庆被害事件,围绕此一事件造成的权力真空,中央政权、地方政权、地方实力派与藏族各界展开博弈。抗战方兴,中央政权对待边疆民族宗教问题的策略是努力保持大后方稳定,而地方实力派鲁大昌却力主改土归流,藏族上层人士则居间折冲,实际上主张保留土司制度。地方政权借助军事威慑,恩威并用,以保留形式上的土司制度羁縻藏族上层,以建立地方政权系统逐步进行渗透。     

Uniformly adaptive estimation for models with arma errors

A semiparametric estimator based on an unknown density isuniformly adaptive if the expected loss of the estimator converges to the asymptotic expected loss of the maximum liklihood estimator based on teh true density (MLE), and if convergence does not depend on either the parameter values or the form of the unknown density. Without uniform adaptivity, the asymptotic expected loss of the MLE need not approximate the expected loss of a semiparametric estimator for any finite sample I show that a two step semiparametric estimator is uniformly adaptive for the parameters of nonlinear regression models with autoregressive moving average errors.