Accurate computation of single and product moments of order statistics under progressive censoring

An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable.     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

“动物与人”：叙事伦理、悖反性与双重困境指向——论“抉择之痛”作为功能指涉的效力边际

对初始情境中受难者“陷困”功能的探讨，是“动物叙事”叙事语法研究中不容忽视的一环，其中贯穿了一个最为基础的叙事功能指向——“抉择之痛”。强调“动物与人”两类受难者角色在身体、心理抑或情感维度陷入某种矛盾与纠结的状态，并且彼此间时常呈现出一定的矛盾悖反性。这一角色身份由动物形象与人类形象分别或共同承担，均指向一种叙事伦理层面的现代境遇的表达。在题材范畴方面，这一功能指涉涵盖了家养类与野生类“动物叙事”各自的叙事范畴。其效力边际已不仅仅局限在单纯生态视域与人性指涉的层面，而是凸显现代语境下人类所面临的共通性的伦理困境：一种挥之不去的矛盾、困惑与不安的情感和心境的写照。     

制度风险的法律维度: 突破非物质文化遗产保护的瓶颈

以风险理论审视非物质文化遗产的现行法律制度,根据风险产生根源不同,非物质文化遗产保护的制度风险会表现为制度运转失灵风险、制度功能偏差风险和公平性缺失风险。化解制度风险,形成制度风险的维度,不可基于同一个标准,而是需要在大的框架之下论及制度风险的法律管控,需要有针对性地创构"建立私权,善用公权"的多元法律控制体系,并在体系内引入技术规制,创设"非物质文化遗产权",推动民间习惯法与法律制度、公法与私法的互动式发展。     

从《了凡四训》到《训儿俗说》——关于袁了凡及其家风家训的思想史考察

袁了凡（袁黄）以其《了凡四训》闻名于世，该书亦被当作训子家书。其实，了凡所作家训并非《了凡四训》，而是《训儿俗说》。作为王龙溪（王畿）的及门弟子，了凡在思想上是阳明后学的一分子，其人生轨迹属于典型的儒家士大夫，其日常修持及著述呈现三教汇通的思想特色。了凡家风淳朴，家学深厚，以儒为宗，兼收并蓄，强调道德主义，注重积德行善，具有出世情怀，对其人格产生深刻影响。     

Probabilistic population projections for countries with generalized HIV/AIDS epidemics

In 2015, the United Nations (UN) issued probabilistic population projections for all countries up to 2100, by simulating future levels of total fertility and life expectancy and combining the results using a standard cohort component projection method. For the 40 countries with generalized HIV/AIDS epidemics, the mortality projections used the Spectrum/Estimation and Projection Package (EPP) model, a complex, multistate model designed for short-term projections of policy-relevant quantities for the epidemic. We propose a simpler approach that is more compatible with existing UN projection methods for other countries. Changes in life expectancy are projected probabilistically using a simple time series regression and then converted to age- and sex-specific mortality rates using model life tables designed for countries with HIV/AIDS epidemics. These are then input to the cohort component method, as for other countries. The method performed well in an out-of-sample cross-validation experiment. It gives similar short-run projections to Spectrum/EPP, while being simpler and avoiding multistate modelling.     

Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice

The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I–I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I–I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term “essential entities” includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state‐space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS.     

China’s Choice of Analytical Models for Its Anti-Monopoly Law

Modern analytical models for anti-monopoly laws are a core element of the application of those laws. Since the Anti-Monopoly Law of the People’s Republic of China was promulgated in 2008, law enforcement and judicial authorities have applied different analytical models, leading to divergent legal and regulatory outcomes as similar cases receive different verdicts. To select a suitable analytical model for China’s Anti-Monopoly Law, we need to consider the possible contribution of both economic analysis and legal formalism and to learn from the mature systems and experience of foreign countries. It is also necessary to take into account such binding constraints as the current composition of China’s anti-monopoly legal system, the ability of implementing agencies and the supply of economic analysis, in order to ensure complementarity between the analytical model chosen and the complexity of economic analysis and between the professionalism of implementing agencies and the cost of compliance for participants in economic activities. In terms of institutional design, the models should provide a considered explanation of the legislative aims of the law’s provisions. It is necessary, therefore, to establish a processing model of behavioral classification that is based on China’s national conditions, applies analytical models using normative comprehensive analysis, makes use of the distribution rule of burden of proof, improves supporting systems related to analytical models and enhances the ability of public authorities to implement the law.     

朱熹和孟子解读舜之“怨慕”的不同逻辑

对于舜之“怨慕”,朱熹作出了不同于孟子的解读。这是基于心学、理学内在逻辑的不同。孟子作为私学之儒,和孔子一样,是主张士君子的阳刚人格的,并且从性向善的人性论出发,协调义与利、公与私的关系,而以君臣父子关系都属对待关系;依此,将舜之“怨慕”解读为舜对父母的既怨又慕。朱熹则作为官学之儒,以所谓“气质之性”协调理学先驱荀子的性向恶论,以二歧化思维把天地之性、天理绝对化,以公去私,视君臣父子关系则为下对上的绝对服从关系;依此解读,舜之“怨”只能是自怨。     

On the estimation of non linear functions in stochastic volatility models

Abstract

This paper focuses on the inference of suitable generally non linear functions in stochastic volatility models. In this context, in order to estimate the variance of the proposed estimators, a moving block bootstrap (MBB) approach is suggested and discussed. Under mild assumptions, we show that the MBB procedure is weakly consistent. Moreover, a methodology to choose the optimal length block in the MBB is proposed. Some examples and simulations on the model are also made to show the performance of the proposed procedure.