Optimum linear unbiased estimation of the scale parameter by absolute values of order statistics in the double exponential and the double weibull distributions

The first two moments and product moments of absolute values of order statistics are obtained for the double exponential and the double Weibull distributions. In both of the distributions an optimum linear unbiased estimator of the scale parameter, by absolute values of the order statistics, is obtained from complete and censored samples of size n=3(1)10. It is found that the new estimator is generally more efficient than the best linear unbiased estimator (BLUE) of the scale parameter by order statistcs in both of the distributions.     

On Least Absolute Value Estimators for Poisson Processes

We consider the problem of parameter estimation for an inhomogeneous Poisson process observed on the time interval [0, τ]. We introduce the minimum L ₁-norm estimator of the unknown parameter and study the asymptotical behaviors of the estimates when the number of observations increases. It is established that this estimator is consistent and we show that the corresponding differences converge to certain variables. These limit variables are asymptotically normal as τ tends to infinity.     

Graphical Demonstration of an Optimality Property of the Median

The property that the mean absolute deviation is a minimum when measured from a median is demonstrated with graphs. Deficiencies of the usual proof of the property are pointed out, and a new, general proof is suggested.     

Least absolute value regression: a special case of piecewise linear minimization

The Barrodale and Roberts algorithm for least absolute value (LAV) regression and the algorithm proposed by Bartels and Conn both have the advantage that they are often able to skip across points at which the conventional simplex-method algorithms for LAV regression would be required to carry out an (expensive) pivot operation.

We indicate here that this advantage holds in the Bartels-Conn approach for a wider class of problems: the minimization of piecewise linear functions. We show how LAV regression, restricted LAV regression, general linear programming and least maximum absolute value regression can all be easily expressed as piecewise linear minimization problems.     

罗斯福与约翰逊政府社会保障政策比较

罗斯福政府与约翰逊政府推行社会保障的社会背景、社会保障的思想及社会保障的实践有很大的不同.罗斯福是美国社会保障制度的开拓者,其社会保障政策具有安全阀的作用.约翰逊是这一政策的发展者,其社会保障政策具有调节器和润滑剂的作用.     

人的全面发展也是硬道理--解读中国共产党的人文思想

以人为本,促进人的全面发展是一个美好的理想,需要经历一个很长的过程,才可以接近这个目标。在这个过程的起始点上,首先要解决人的基本生存问题,其次是促进人的全面发展问题。受中国文化和客观环境的制约,这一过程表现了中国独特的进步路径。     

黑格尔的宗教神学观与哲学史的联系

黑格尔的社会思想包含着非常复杂的思想元素。既有希腊哲学家的思想成分,又有新柏拉图主义的思想成分。同时,神秘主义哲学和基督教思想也都对他产生过影响。他的宗教哲学包容了所有的这些思想形态。     

Frontiers of Stochastically Nondominated Portfolios

We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution.We propose mean‐risk models that are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second‐order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean‐risk efficient frontiers of these models and we illustrate its operation on a large data set involving thousands of assets and realizations.     

重贤不尚贤用贤且防贤--韩非贤能观初探

韩非的贤能观以维护君主独裁专制的法治理论为基础。韩非虽充分肯定贤能在辅佐君主建功立业中的重要作用,但同时也严厉抨击了战国时期“上贤任智无常”造成弑君篡位的弊端,“上 (尚)法不上 (尚)贤”,用贤以“明法”为的彀是韩非贤能观的本质。举贤任能,韩非主张以“参伍之道”察言识人,以“隐栝之道”大量使用一般人才,坚持原则反对用人的不正之风。使贤用能,韩非强调以法治官与用术禁奸相结合,充分调动百官尽忠尽责的积极性。