Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.     

Joint product assortment,inventory and price optimization to attract loyal and non-loyal customers

In this paper, we analyze the emerging retail practice of carrying a combined product assortment consisting of both regular “standard” products and more fashionable and short-lived “special” products. The purpose of this practice is to increase store traffic by attracting heterogeneous classes of customers, which drives up sales of standard products due to the potential cross-selling effect. Customers who are primarily attracted by special products will also buy some standard products. In this context, we analyze three decisions that are crucial for a retailer׳s commercial success: the product assortment, the inventory levels and the pricing. We propose an optimization model and an iterative heuristic to analyze the trade-offs between the combined product assortment, the inventory level and the price per product when there is limited shelf space. Using numerical experiments, we show that our heuristic can be trusted and that its accuracy improves when the number of products increases. Our findings indicate that to attract more customers for standard products, a retailer may benefit from carrying low priced special products which, if considered in isolation, would be non-profitable. As the cross-selling effect decreases, a retailer should focus more on the standard assortment by increasing its size and decreasing the prices. However, introducing special products and ignoring the cross-selling effect may decrease a retailer׳s profitability. We show that the introduction of special products involves more than just choosing the right specials for non-loyal customers but impacts the global assortment planning, the standard products and the products pricing.     

问题类型划分方法视野下的犯罪概念研究

在问题类型划分方法的视野下,犯罪概念问题应该属于纯粹刑法学问题中的解释选择问题,但刑法学界以往有关犯罪概念的讨论却大多将其作为刑法问题中的价值判断问题。由于未能妥当确定犯罪概念的问题类型,从而使学界有关犯罪概念的讨论未能达成最低限度的学术共识。作为纯粹刑法学问题中的解释选择问题,形式与实质相结合的混合犯罪概念不存在被替代的必要性,而犯罪概念也不应被规定在刑法典中。     

论广州城市生活垃圾治理的战略取向

现代城市垃圾治理是一项复杂的系统工程。在城市垃圾中,生活垃圾所占比重大、与民众联系密切且处理阻力大,对城市生活垃圾治理的战略设计已成为城市管理者面临的最大难题之一。作为我国重要中心城市的广州,也正面临形势严峻的"垃圾围城"之困,自2012年开启新一轮城市生活垃圾综合治理以来,在有创新、有收获的同时也遇到了新的挑战。为进一步深化城市生活垃圾治理工作,广州应准确把脉顶层制度难"落地"、流程运行难系统、民众习惯难转变等现实症结,科学设计生活垃圾的多元共治路径,实现挑战与机遇的对接,为我国城市生活垃圾的治理树立标杆,助推开创城市垃圾治理的新局面。     

Multiple-class classification: Ordinal and categorical labels

We study multiple-class classification problems. Both ordinal and categorical labeled cases are discussed. The common approaches for multiple-class classification are built on binary classifiers, in which one-versus-one and one-versus-rest are typical approaches. When the number of classes is large, then these binary-classifier-based methods may suffer from either computational costs or the highly imbalanced sample sizes in their training stage. In order to alleviate the computational burden and the imbalanced training data issue in multiple-class classification problems, we propose a method that has competitive performance and retains the ease of model interpretation, which is essential for a prognostic/predictive model.     

Aggregating classifiers via Rademacher–Walsh polynomials

Methods are proposed to combine several individual classifiers in order to develop more accurate classification rules. The proposed algorithm uses Rademacher–Walsh polynomials to combine M (≥2) individual classifiers in a nonlinear way. The resulting classifier is optimal in the sense that its misclassification error rate is always less than, or equal to, that of each constituent classifier. A number of numerical examples (based on both real and simulated data) are also given. These examples demonstrate some new, and far-reaching, benefits of working with combined classifiers.     

试述北魏宗室阶层的犯罪类型

北魏宗室阶层是政权的柱石、统治集团的核心,在政治和社会领域里享受充分的特权,北魏时期的法律反映了宗室特权的主要方面.由于拓跋鲜卑历经由游牧部落向文明国家阶段的跃进,宗室成员在身份角色的转换过程中不可避免地会与国家法制和名教礼法发生冲突,表现为具体的犯罪行为.北魏宗室非违主要有政治犯罪、职务犯罪、刑事犯罪和悖逆纲常伦理四类.各类罪行的时间分布特点和惩治力度集中反映出宗室生存境遇的改变和王朝政局的走势.     

India's demand for international reserve and monetary disequilibrium: Reserve adequacy under floating regime

The main aim of this study is to investigate India's demand for international reserve by focusing on the role of national monetary disequilibrium and to present new benchmarks for assessing the adequacy of international reserves. We assessed India's position in terms of reserve adequacy and found that India is well placed and has sufficient stock of international reserves to meet the minimum adequacy requirements. Also, the results reveal that the central bank is holding substantial excess reserves and the related opportunity cost (1.5% of GDP) appears to be quite considerable. Further, the estimates of reserve demand function suggest that scale of foreign trade, uncertainty and profitability considerations play significant role in determining India's long-term reserve demand policies. More importantly, validating the monetary approach to balance of payment, our results show that national monetary disequilibrium does play a crucial role in short-run reserve movements. An excess of money demand (supply) induces an inflow (outflow) of international reserves with an elasticity of 0.56 which also implies that Reserve Bank of India responds to correct the domestic money market disequilibrium; and did not just leave it completely on the mercy of reserve inflows.     

Second-Order Approximations to Two Classes of Sequential Estimation Procedures

For the model considered by Chaturvedi, Pandey and Gupta (1991), two classes of sequential procedures are developed to construct confidence regions (which may be interval, ellipsoidal or spherical) of ‘pre-assigned width and coverage probability’ for the parameters of interest and for the minimum risk point estimation (taking loss to be quadratic plus linear cost of sampling) of the nuisance parameter. Second-Order approximations are derived for the expected sample size, coverage probability and ‘regret’ associated with the two classes of sequential procedures. A simple and direct method of obtaining the asymptotic distribution of the stopping time is provided. By means of examples, it is illustrated that several estimation problems can be tackled with the help of proposed classes of sequential procedures.