论合同欺诈的成因及对策

利用合同进行欺诈的案件给市场经济的发展带来了灾难性的后果。合同欺诈行为产生的原因是多方面的 ,单靠加大打击力度并不能从根本上解决问题 ,只有认真分析合同欺诈产生的个人、社会、经济原因 ,进行综合治理 ,才能从根本上遏制合同欺诈 ,促进市场经济的发展。     

论贷款诈骗罪主体

我国刑法把单位排除在贷款诈骗罪的犯罪主体之外是立法的明显漏洞,也不符合司法实践的需要.事实上,诈骗罪与其所派生的金融诈骗、合同诈骗、贷款诈骗等犯罪是种属关系,它们之间存在法条竞合的情形,而合同诈骗罪与贷款诈骗罪并列同属诈骗罪的特殊法条.因此,在刑法修改之前,对单位贷款诈骗行为应依法以贷款诈骗罪追究有关直接负责的主管人员和其他责任人员的刑事责任.当然,在量刑时要体现原则性与灵活性相结合的原则.     

On adaptive estimation

Point estimates that are weighted averages of other estimates are considered. They are adaptive because the weights are also functions of the sample observations.In particular, the weights are functions of new measures of peakedness and skewness. Five adaptive estimators are compared (in a Monte Carlo study using the swindle) to some of the usual estimators, including those robust ones of Huber and Tukey. In addition, the swindle constant is considered in some detail. All of the adaptive estimators do extremely well with an adaptive biweight statistic being the best one in this study. Suggestions are made about future directions in this area.     

Adaptive m estimation of symmetric distribution location

An adaptive M esitmation procedure for using a random sample to estimate the location parameter of an unknown symmetric distribution is developed. The procedure may be applied to samples from distributions with tail lenghts at least as heavy as normal distribution tails. Simulation studies demonstrate the potential of the new estimator for producing good location estimates.     

合同诈骗罪探讨

合同诈骗罪是从普通诈骗罪中分裂出来的新型经济犯罪,它在保留了普遍诈骗罪的一些共性特征外又表现出自身的个性,这种个性主要体现在共罪构成的特殊性,鉴于本罪认定过程的复杂性,本文对司法实践中注意的几个问题(非法占有目的认定问题,罪数问题,共犯问题)作了剖析,以期有助于司法实践中准确把握此罪认定。     

A comparison of methods for studentizing the sample median

Various methods for “Studentizing” the sample median are com-pared on the basis of a Monte Carlo study. Several of the methods do rather poorly while two, the bootstrap and the standardized length of a distribution free confidence interval, behave accept-ably acrors a wide range of sample sizes and several distributions of varying tail length. These two methods seem to agree closely with the distribution free confidence intervals and moreover, un-like these intervals, the methods can be extended to a method of accurate inference for λ₁ regreasion.     

保险诈骗罪疑难问题研究

1997年修订的《中华人民共和国刑法》第198条规定了保险诈骗罪,使保险诈骗罪成为金融诈骗犯罪中的重要犯罪之一。应当承认的是,由于这一立法起步较晚,仍然有一些值得深入探讨的难题。主要表现在:对目的性要件的理解、单位主体的并罚、未遂问题、非法定共犯的定罪,都是见仁见智,莫衷一是。本文对上述疑难问题作了深入的研究和探讨,希望对司法认定有所帮助。     

Control variates for monte carlo analysis of nonlinear statisticalmodels. IV

A Monte Carlo control variate method is used to study the estimators obtained in nonlinear regression under nonnormal error distributions. Two forms of the standard linear approximator are used as the control variates: a natural approximator using the nonnormal errors sampled, and a normalized approximator obtained by transformation of the errors. The natural approximator is shown to be most effective when the sampling distribution is itself nonnormal; its effectiveness is well approximated by a function of the Beale measure of nonlinearity. The normalized approximator is most effective when the estimator sampling distribution is approximately normal. A one-parameter model is used for illustration with uniform and gamma distributed errors     

Control Variates for Monte Carlo Analysis of Nonlinear Statistical Models,I: Overview

Parameter values of nonlinear statistical models are typically estimated from data using iterative numerical procedures. The resulting joint sampling distribution of the parameter estimators is often intractable, resulting in the use of approximators or Monte Carlo simulation to determine properties of the sampling distribution.

This paper develops methods, using linear and higher-order approximators as control variates that reduce the variance of the Monte Carlo estimator by orders of magnitude. Estimation of means, higher-order raw moments, variances, covariances, and percentiles is considered.     

Estimation of the sum of differences distribution

Consider the distribution of Z_i d_iwhere the d.d_i?s are 1=1 lldifferences independently, identically and symmetrically distributed with mean zero. The problem is to determine properties of the sdd given the distribution of the d._i?fs and the sample size n. The standardized moments as a function of the moments of the d._i!s are developed. A variance reduction technique for estimating the quantiles of the sdd using Monte Carlo methods is developed based on using the randomization sample consisting of the 2ⁿ values of Z _i+d. rather than the single observation i=l lZ d. corresponding to each sample d_id_n. The randomization sample is shown to produce unbiased and consistent estimators.