A modified nested-error regression model for small area estimation

A nested-error regression model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a proportion of domains where the variable of interest cannot be described by a standard linear mixed model. Algorithms and formulas to fit the model, to calculate EBLUP and to estimate mean-squared errors are given. A Monte Carlo simulation experiment is presented to illustrate the gain of precision obtained by using the proposed model and to obtain some practical conclusions. A motivating application to Spanish Labour Force Survey data is also given.     

A note on optimum linear feature extraction for gaussian populations with equal covariances and equal a priori probabilities

We consider the linear feature selection problem of obtaining a nonzero 1 × n matrix B which minimizes the probability of misclassification based on the Bayes decision rule applied to the random variable Y = BX, where X is a random n-vector arising from one of m Gaussian populations with equal covariances and equal apriori probabilities. It is shown that the optimal B satisfies a fixed point equation B = F(B) which can be solved by successive substitution.     

Approximate regression models and splines

The literature pertaining to splines in regression analysis is reviewed. Spline regression is motivated as a simple extension of the basic polynomial regression model. Using this framework, the concepts of fixed and variable knot spline regression are developed and corresponding inferential procedures are considered. Smoothing splines are also seen to be an extension of polynomial regression and various optimality properties, as well as inferential and diagnostic methods, for these types of splines are discussed.     

Optimal bayesian confidence interval of fixed width

We obtain the optimal fixed width Bayes confidence interval (optimal in the sense that the posterior probability of 8 being in the interval is maximum) for the parameter 6 , when the posterior distribution of ?^-1 , given the data is known to be a truncated gamma distribution.     

On linear statistical models of commutative quadratic type

By defining a special class of vector decompositions we consider linear statistical models of commutative quadratic type, which especially cover balanced complete and incomplete ANOVA models with fixed, random and mixed effects. Under the assumption of normal distribution we are concerned with distributions of general quadratic forms, with point and confidence region estimation as well as with hypothesis testing for fixed effects (including multiple comparisons) and variance components.     

政策无奈性:对货币政策效力的一种表述

与货币政策有效性相对的是政策无效性,而政策无效性更深的层面是政策无奈性。在如何调控固定资产投资规模和速度的问题上,中央银行的货币政策在许多时候表现出"无奈性"。通过对货币政策无奈性存在原因的剖析,从中认识其对经济稳定发展的影响,并得出改变中央银行独立性类型的结论。     

农业总产值指数影响因素的模型分析--以江西省为例

江西是我国的农业大省。运用农业总产值指数影响因素的模型分析可知:1970—1998年间,江西农业生产中的科技含量偏低,农作物的播种面积对农业总产值的影响最为显著,化肥施用量其次,而政府对农业生产和事业财政支持的影响最小。     

浅谈高校固定总价合同包干工程的审计

当前,高校都很重视基建工程审计,但对固定合同总价工程的审计却未涉及或涉及很少。高校固定合同总价工程的审计,首先是要做好工程招投标阶段的审计,认真审核招标文件、标底及参与招投标的过程,从源头控制;其次要做好合同签订阶段的审计,使项目实施阶段和工程结算阶段的审计能有章可循。为此,从固定合同总价工程的招投标阶段、合同签订阶段、实施阶段和工程结算阶段论述了固定合同总价工程审计的必要性及内容、方法。     

高校固定资产会计管理的问题

通过对现行高校固定资产会计处理方法的分析 ,针对高校在购置固定资产 ,以固定资产对外投资 ,以及固定资产是否提取折旧等方面存在的处理方法不当等问题 ,指出固定资产价值损耗未及时得到补偿和补偿方法缺乏科学合理依据。提出改进高校固定资产核算的方法 ,从而达到保证高校固定资产的核算更加科学准确的目的     

“路径依赖”与中国古代的重农抑商制度

"路径依赖"在中国古代重农抑商制度的形成、发展中发挥了重要作用.战国时期,重农、抑商思想开始有机结合并有所发展,与其有关的制度建设在秦国取得成功;秦朝继承、发展了重农抑商制度;在西汉,这项制度得到了充分检验,并形成了制度选择到制度确立的制度变迁模型.由于"路径依赖"的存在,这一模型在中国经济制度史上产生了重要影响.