Reducing component estimation for varying coefficient models

The estimation problem for varying coefficient models has been studied by many authors. We consider the problem in the case that the unknown functions admit different degrees of smoothness. In this paper we propose a reducing component local polynomial method to estimate the unknown functions. It is shown that all of our estimators achieve the optimal convergence rates. The asymptotic distributions of our estimators are also derived. The established asymptotic results and the simulation results show that our estimators outperform the the existing two-step estimators when the coefficient functions admit different degrees of smoothness. We also develop methods to speed up the estimation of the model and the selection of the bandwidths.     

On the type-B integral equation and the distribution of wilks statist for testing independence of several groups of variables

In this paper, WILKS'type-B integral equation is solved in the general form of a series of beta functions and a series of weighted gamma functions as proposed by WALD and BROOKNER 1941. The coefficients in both representations can be obtained by explicit recurrence relartions, therefore the results solve many distributional problems and have the fewest computational difficulties of any representation that has surfaced to date. The radius of convergence of the second series representation is given, whereas the convergence property of the first series representation is given, whereas the convergence property of the first series representation was studied by WALD and Brookner. The exact null distributions of WILKS' statistic A for testing the independence of several groups of variables and of V = -log A are given. The coefficients in all the series representration can be computed recursilvely and hence can be obtained easily with the help of modern computatinal facilities     

Dynamic optimal capital growth of diversified investment

We investigate the problem of dynamic optimal capital growth of diversified investment. A general framework that the trader maximize the expected log utility of long-term growth rate of initial wealth was developed. We show that the trader's fortune will exceed any fixed bound when the fraction is chosen less than critical value. But, if the fraction is larger than that value, ruin is almost sure. In order to maximize wealth, we should choose the optimal fraction at each trade. Empirical results with real financial data show the feasible allocation. The larger the fraction and hence the larger the chance of falling below the desired wealth growth path.     

Copula‐based semiparametric analysis for time series data with detection limits

The analysis of time series data with detection limits is challenging due to the high‐dimensional integral involved in the likelihood. Existing methods are either computationally demanding or rely on restrictive parametric distributional assumptions. We propose a semiparametric approach, where the temporal dependence is captured by parametric copula, while the marginal distribution is estimated non‐parametrically. Utilizing the properties of copulas, we develop a new copula‐based sequential sampling algorithm, which provides a convenient way to calculate the censored likelihood. Even without full parametric distributional assumptions, the proposed method still allows us to efficiently compute the conditional quantiles of the censored response at a future time point, and thus construct both point and interval predictions. We establish the asymptotic properties of the proposed pseudo maximum likelihood estimator, and demonstrate through simulation and the analysis of a water quality data that the proposed method is more flexible and leads to more accurate predictions than Gaussian‐based methods for non‐normal data. The Canadian Journal of Statistics 47: 438–454; 2019 © 2019 Statistical Society of Canada     

What is this moment we are caught in?

Our response to the question ‘What is this moment we are caught in?' is articulated through our collaborative reading of Berlant's (2011) Cruel Optimism (Durham, NC: Duke University Press). Cruel optimism, Berlant suggests, is a desire for something that undermines its own potentiality. As queer academics we expose the cruelty of our desires to live a good academic life, and we do so from our different positions as postdoctoral fellow, tenured academic and PhD candidate. In labouring to consolidate relationships and practices that hold the promise of our own sustainability, we give accounts of the material and affective work we perform to constitute what Berlant calls an intimate public, a collective space of mediation that functions as a key tactic to manage our academic life. These accounts take the form of three vignettes, each inflected by the specificities of our different positions and histories of becoming academics. We use Berlant as a point of departure to both interrogate practices of self‐management and find possibilities for a collective response to the moments in which we find ourselves caught.     

水下测试树国内外研究现状与国产化思考

水下测试树是深水测试过程中风险控制的关键性设备，在特殊海况时具有快速断开测试管柱、封堵井下管柱内高压油气以达到保护测试仪器和人员安全以及避免海洋环境污染的作用。通过大量文献资料收集和现场调研，分析了水下测试树的国内外研究现状，详细介绍了国外水下测试树的功能、结构特点、应用情况及国内水下测试树的发展与应用情况。对比分析表明：国外水下测试树现有产品功能强大、性能可靠、适用于不同海洋工况，且不同公司的产品在结构和功能上各具特点。同时，针对国内水下测试树的应用现状，提出了水下测试树国产化的研究思路以及研究开发过程中可能出现的问题，对促进我国海洋石油水下装备自主研发与制造具有重要意义。     

非线性时滞差分方程解的振动性

讨论了时滞差分系统yn＋1－yn＋Pnf（yn－k）＝0n＝0,1,2,...（y≠0）的振动性,得到了上式方程解振动的一组充分条件．     

组织信息资源管理论纲

本文在简要分析现代组织管理环境基本特点的基础上,对社会组织的信息资源管理的功能、原则及其运作等若干问题进行了认真的探讨,以期进一步完善现代组织管理理论。     

论“代际储存”——代际正义的一个重要问题

代际储存,是代际正义的一个重要问题。它是以代际正义为伦理导向,以环境资源为主要对象,以解决环境危机为基本目标,以实现人类可持续生存发展为终极目的的制度化分配原则。它的实施,既是建设生态文明社会的必由之路,也是解决当前全球性生态危机,实现可持续发展的重大举措。