论刑事证据的法律分类

本文对刑事证据的“种类”、“分类”之称谓进行辨析,认为两者实质含义一致,进而提出采 用“法律上的分类”与“理论上的分类”的观点。作者立足我国刑事证据的立法分类,分析其规定不足, 建议重新分类,特别指出刑事证据分类应注视一、二审的转化问题和与今后将建立的证据规则相衔接 问题。     

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.

In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.     

Banking on fewer children: financial intermediation,fertility and economic development

This paper shows that financial intermediation can influence fertility and labor allocation decisions by raising market wages. The increase in wages induces some households to abandon “traditional” labor intensive methods of production managed at the household level and supply labor to “modern” sector firms. Since it is optimal for households in the modern sector to have fewer children, the labor allocation decision leads to lower national fertility. A panel VAR using financial intermediation, fertility and industrial employment share data in 87 countries is estimated. The empirical results show that the data are consistent with the theoretical predictions. Received: 20 October 1997/Accepted: 31 August 1998     

Risk attitudes and risky behavior

In economic theory, risk aversion is a characteristic of the typical utility function of money. Observations of how people deal with risks in real life have cast some doubts on the prevalence of risk aversion. People buy insurance, but they also gamble and take investment risks. Many of the conclusions in the discussions of utility derive from experiments employing some kind of lottery choices. While the experiments have given interesting ideas for theory, there has been little testing of the extent to which the obtained measures of risk attitudes correlate with actual behavior. Data from the VSB panel were used to answer three questions: (1) Can hypothetical risky choice questions be meaningfully answered by ordinary survey respondents? (2) What are the relationships between different measures of risk attitudes and actual portfolio choices of risky assets? (3) What is the relationship between risk attitude and playing in lotteries, lotto, etc.?     

唐代小说作者类属分析

唐代 ,是“始有意为小说”的时期。受当时“尚奇好异”思想影响 ,人们乐于创作、编辑、传播小说 ,从而促成了唐代小说的空前繁荣。唐代小说不但质高量丰 ,且多署有作者真实姓名 (或不难考定姓名 ) ,这与古代其他时期的情形大不相同。以唐代小说作者为对象、以其“身份”、“类属”为范围作一梳理 ,从中可见唐人小说繁荣因缘根基之一斑。     

Convexity-based clustering criteria: theory,algorithms, and applications in statistics

This paper deals with the construction of optimum partitions of for a clustering criterion which is based on a convex function of the class centroids as a generalization of the classical SSQ clustering criterion for n data points. We formulate a dual optimality problem involving two sets of variables and derive a maximum-support-plane (MSP) algorithm for constructing a (sub-)optimum partition as a generalized k-means algorithm. We present various modifications of the basic criterion and describe the corresponding MSP algorithm. It is shown that the method can also be used for solving optimality problems in classical statistics (maximizing Csiszárs -divergence) and for simultaneous classification of the rows and columns of a contingency table.     

Conditional Generalized Liouville Distributions on the Simplex

Liouville and generalized Liouville distributions on the simplex have been proposed for modeling compositional data and have been shown to be free from the extreme independence structure that characterizes the Dirichlet class. In this article, generalized Liouville distributions are shown to be rich enough to distinguish some lesser modes of independence as well. Unfortunately, it is noted that the applicability of the Liouville family will be limited, owing to the lack of invariance with respect to the chosen fill-up value. As an alternative, a new family of simplex distributions is proposed, one that admits invariance with respect to choice of fill-up value, as well as the ability to differentiate among many forms of independence.     

The cost of children: May the collective approach to household behavior help?

The collective approach to household consumption behavior tries to infer from variables supposed to affect the general bargaining position of household members information on the allocation of consumptions goods and tasks among them. This paper investigates the extension of previous work to the case where children may be considered as a public consumption good by the two adult members of a household. The main question being asked is whether it is possible to retrieve from the aggregate consumption behaviour of the household and the relative earnings of the parents information on the allocation of goods between them and children. This alternative approach to the estimation of the ‘cost of children’ is contrasted with the conventional approach based on a ‘unitary’ representation of and demographic separability assumptions on household consumption behaviour. Received: 29 August 1997/Accepted: 26 November 1998     

Sparse Bayesian variable selection in multinomial probit regression model with application to high-dimensional data classification

Here we consider a multinomial probit regression model where the number of variables substantially exceeds the sample size and only a subset of the available variables is associated with the response. Thus selecting a small number of relevant variables for classification has received a great deal of attention. Generally when the number of variables is substantial, sparsity-enforcing priors for the regression coefficients are called for on grounds of predictive generalization and computational ease. In this paper, we propose a sparse Bayesian variable selection method in multinomial probit regression model for multi-class classification. The performance of our proposed method is demonstrated with one simulated data and three well-known gene expression profiling data: breast cancer data, leukemia data, and small round blue-cell tumors. The results show that compared with other methods, our method is able to select the relevant variables and can obtain competitive classification accuracy with a small subset of relevant genes.     

Personal income taxation under mobility, exogenous and endogenous welfare weights, and asymmetric information

This paper analyses how governments should tax labour income accruing to a group of highly skilled and geographically mobile individuals who divide their time or career between several jurisdictions. The analysis differs from previous models on migration and taxation by addressing optimal regulation when agents work for several principals. Optimal taxation is developed for social welfare functions with exogenous and endogenous welfare weights. Marginal income taxes are applied for screening purposes, and the rates are lower with endogenous than with exogenous welfare weights. Received: 22 January 1998/Accepted: 3 July 1999)