论盗窃犯罪中价值认识错误

盗窃犯罪是一种常见犯罪。实践中对盗窃犯罪存在一些价值认识错误 ,常把盗窃犯罪的“数额”作为认定盗窃行为罪与非罪、罪轻罪重的关键因素 ,片面强调了犯罪认定的客观方面 ,忽视了行为人主观认识错误对犯罪构成的影响 ,从而背离了犯罪认定的主客观统一的原则     

Measurement error, skewness, and risk analysis: coping with the long tail of the distribution.

Probabilistic risk analyses often construct multistage chance trees to estimate the joint probability of compound events. If random measurement error is associated with some or all of the estimates, we show that resulting estimates of joint probability may be highly skewed. Joint probability estimates based on the analysis of multistage chance trees are more likely than not to be below the true probability of adverse events, but will sometimes substantially overestimate them. In contexts such as insurance markets for environmental risks, skewed distributions of risk estimates amplify the "winner's curse" so that the estimated risk premium for low-probability events is likely to be lower than the normative value. Skewness may result even in unbiased estimators of expected value from simple lotteries, if measurement error is associated with both the probability and pay-off terms. Further, skewness may occur even if the error associated with these two estimates is symmetrically distributed. Under certain circumstances, skewed estimates of expected value may result in risk-neutral decisionmakers exhibiting a tendency to choose a certainty equivalent over a lottery of equal expected value, or vice versa. We show that when distributions of estimates of expected value are, positively skewed, under certain circumstances it will be optimal to choose lotteries with nominal values lower than the value of apparently superior certainty equivalents. Extending the previous work of Goodman (1960), we provide an exact formula for the skewness of products.     

宏观经济指标与上证综指长短期走势的预测

上证综合指数和宏观经济指标,如广义货币供应量、国内生产总值、出口与进口的比值,以及外商直接投资之间存在长期的均衡关系,可以通过宏观经济指标来预测上证综合指数的长期走势。误差修正模型的估计结果表明,上证综合指数具备经济"晴雨表"的功能。     

Missing at random (MAR) in nonparametric regression - A simulation experiment

The additive model is considered when some observations on x are missing at random but corresponding observations on y are available. Especially for this model, missing at random is an interesting case because the complete case analysis is expected to be no more suitable. A simulation experiment is reported and the different methods are compared based on their superiority with respect to the sample mean squared error. Some focus is also given on the sample variance and the estimated bias. In detail, the complete case analysis, a kind of stochastic mean imputation, a single imputation and the nearest neighbor imputation are discussed.     

传统计划体制下的管理目标谬误与企业改革

运用系统分析法、功能分析法和案例分析法,研究我国传统计划体制如何通过影响经济系统的管理目标定位从而影响经济运行效率的问题.提出传统计划体制下"管理目标谬误"的概念,分析了管理目标谬误产生的原因和经济运行后果,从而揭示了经济体制通过管理系统的目标定位影响经济效率的内在本质,也揭示了科学管理与体制改革的辩证关系.文章最后指出,要提高企业效率,必须进行经济体制改革.     

The estimation of derivatives of a nonparametric regression function when the data are correlated

A kernel estimator of a derivative of arbitrary order of a nonparametric average population curve is considered for a correlated-errors model with balanced replicate measurements at each design point. Asymptotic expansions of the mean squared error are derived for two classes of correlation functions in the model. Consistency, choice of smoothing parameter, and rates of convergence are examined for the important special cases of estimating the first and second derivatives.     

A correlation-theoretical interpretation of schur analysis

This paper is heavily leaned on the author's recent investigations concerning SCHUR analysis of non-negative Hermitian block matrices. The parameters of the matrix balls and the triangular choice scheme which describe a non-negative Hermitian block matrix will be interpreted in the framework of correlation theory     

A Class of Estimators Using Auxiliary Information for Estimating Finite Population Variance in Presence of Measurement Errors

This article addresses the problem of estimating the population variance using auxiliary information in the presence of measurement errors. When the measurement error variance associated with study variable is known, a class of estimators of the population variance using auxiliary information has been proposed. We obtain the bias and mean squared errors of the suggested class of estimators upto the terms of order n ^?1, and also optimum estimators in asymptotic sense of the class with approximate mean squared error formula.     

Admissible minimum bias estimation of response surfaces

The minimum bias estimator was introduced as an alternative to the least squares estimator for approximating response functions by low-order polynomials. Here we show how to obtain an admissible estimator with smaller squared bias.     

Kernel estimation of a distribution function

A distribution function is estimated by a kernel method with

a poinrwise mean squared error criterion at a point x. Relation- ships between the mean squared error, the point x, the sample size and the required kernel smoothing parazeter are investigated for several distributions treated by Azzaiini (1981). In particular it is noted that at a centre of symmetry or near a mode of the distribution the kernei method breaks down. Point- wise estimation of a distribution function is motivated as a more useful technique than a reference range for preliminary medical diagnosis.