Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

Constrained allocation problems with single-peaked preferences: An axiomatic analysis

We introduce a new class of problems that contains two existing classes: allocation problems with single-peaked preferences and bankruptcy problems. On this class, we analyze the implications of well-known properties such as Pareto optimality, strategy-proofness, resource-monotonicity, no-envy, equal treatment of equals, and two new properties we introduce, hierarchical no-envy and independence of nonbinding constraints. Unlike earlier literature, we consider rules that allow free-disposability. We present characterizations of a rule we introduce on this domain. We relate this rule to well-known rules on the aforementioned subdomains. Based on this relation, we present a characterization of a well-known bankruptcy rule called the constrained equal awards rule. Received: 22 June 2000/Accepted: 21 March 2002 This paper is based on the first chapter of my Ph.D. thesis submitted to the University of Rochester. I wish to thank my advisor, William Thomson, for helpful comments and suggestions.     

International Tax Competition: A Case for International Cooperation in Globalization

The liberalization of international financial flows and foreign direct investment has induced countries to use diverse measures to attract inflow of foreign capital and foreign direct investment, which is expected to have a positive effect on the growth of GDP and thus a positive effect on social welfare. Tax exemption, reduction of tax rate, tax holiday, or diverse subsidies are some of the most important measures used. In this paper we study international tax cooperation, i.e., countries change and especially reduce tax rate for corporate income or for asset revenues to attract inflow of foreign direct investment. Both theoretical and empirical studies have shown the sensibility of foreign direct investment decision with respect to tax rate differences between home countries and host countries. In general, more inflow of foreign direct investment can be expected if the tax rate of the home country is lower than that of foreign countries. This is the main reason for international tax cooperation. In this paper we propose a simple model to prove the sub-optimal Nash non cooperative solution in a two-country tax-competition game. The model shows that international tax cooperation can improve welfare of the participating countries. How to reach a cooperative solution for an international tax competition game (ITCG) is therefore an important issue for further discussions and studies. International institutions can play a crucial role to reach international tax cooperation or international tax harmonization.     

略论黎简的宗宋倾向及对宋诗派的影响

乾嘉时期的岭南诗人黎简,对道咸年间的宋诗派产生过不为众人知晓的影响。黎简在创作实践上宗法宋诗,其有关创作主张又与宋诗派理论的基本精神近似,这就是他间接影响宋诗派的前提。他通过自身与江浙诗人之间的交叉作用,最终使这种影响成为现实。他上承秀水派的钱载、下启其后贤钱仪吉等。通过这种流派的承传,黎简与宋诗派之间的关联得以发生与凸现,因此,黎简在这一诗体发展演变过程中的这种穿针引线的作用理应得到我们的体认与重视。     

Statistical consulting

The paper and the special issue focus on the activity of statistical consulting and its varieties. This includes academic consulting, consulting to and in industry as well as statistics in public media.