Higher-order Bayesian Approximations for Pseudo-posterior Distributions

The theory of higher-order asymptotics provides accurate approximations to posterior distributions for a scalar parameter of interest, and to the corresponding tail area, for practical use in Bayesian analysis. The aim of this article is to extend these approximations to pseudo-posterior distributions, e.g., posterior distributions based on a pseudo-likelihood function and a suitable prior, which are proved to be particularly useful when the full likelihood is analytically or computationally infeasible. In particular, from a theoretical point of view, we derive the Laplace approximation for a pseudo-posterior distribution, and for the corresponding tail area, for a scalar parameter of interest, also in the presence of nuisance parameters. From a computational point of view, starting from these higher-order approximations, we discuss the higher-order tail area (HOTA) algorithm useful to approximate marginal posterior distributions, and related quantities. Compared to standard Markov chain Monte Carlo methods, the main advantage of the HOTA algorithm is that it gives independent samples at a negligible computational cost. The relevant computations are illustrated by two examples.     

协同创新视角下的学会建设

学会的基本属性和活动方式与协同创新要求相契合,使其能够在推动协同创新、实施科技创新驱动发展战略中发挥重要作用。协同创新是一个复杂的系统工程,学会在政府、科学家、企业、金融资本等创新活动主体间扮演沟通联系人、协调者、润滑剂的角色,构建跨学科、跨大类学科甚至跨文理界限的学会联盟是协同创新活动发展的必然。为提升学会学术研究、协同创新能力,政府部门、企业、高等院校、科研部门、私人基金会等应支持学会建设向着有利于协同创新的方向发展,学会应进一步推动实体化建设,面向市场,服务社会。     

考虑零件三维装载约束带时间窗的循环取货路径问题研究

为提高车辆的可装载性,对考虑三维装载约束带时间窗的循环取货路径问题进行研究.在给定假设与约束条件的前提下,建立该问题的多目标数学模型,并设计用于问题求解的基于改进策略的启发式算法.数值实例的计算结果表明,该算法可有效求解考虑零件三维装载约束带时间窗的循环取货路径问题;且与时间窗优先法的求解结果相比,可大幅提高车辆的可装载性,并能有效减少不同车型车辆的投入数量.     

Computation of an efficient and robust estimator in a semiparametric mixture model

In this article, we propose an efficient and robust estimation for the semiparametric mixture model that is a mixture of unknown location-shifted symmetric distributions. Our estimation is derived by minimizing the profile Hellinger distance (MPHD) between the model and a nonparametric density estimate. We propose a simple and efficient algorithm to find the proposed MPHD estimation. Monte Carlo simulation study is conducted to examine the finite sample performance of the proposed procedure and to compare it with other existing methods. Based on our empirical studies, the newly proposed procedure works very competitively compared to the existing methods for normal component cases and much better for non-normal component cases. More importantly, the proposed procedure is robust when the data are contaminated with outlying observations. A real data application is also provided to illustrate the proposed estimation procedure.     

Fitting competing risks data to bivariate Pareto models

This paper revisits two bivariate Pareto models for fitting competing risks data. The first model is the Frank copula model, and the second one is a bivariate Pareto model introduced by Sankaran and Nair (1993 Sankaran, P. G., and N. U. Nair. 1993. A bivariate Pareto model and its applications to reliability. Naval Research Logistics 40 (7):1013–1020. doi:10.1002/1520-6750(199312)40:7%3c1013::AID-NAV3220400711%3e3.0.CO;2-7.[Crossref], [Web of Science ®] , [Google Scholar]). We discuss the identifiability issues of these models and develop the maximum likelihood estimation procedures including their computational algorithms and model-diagnostic procedures. Simulations are conducted to examine the performance of the maximum likelihood estimation. Real data are analyzed for illustration.     

Nonprofit organizations in between the nonprofit and market spheres: Shifting goals,governance and management?

In spite of the belief instilled by the New Public Management reforms that nonprofit organizations (NPOs) can benefit from more management, more measurement and more market practices, systematic knowledge on the organizational effects of NPOs incorporating business practices in their day‐to‐day functioning remains absent to date. This research note addresses this limitation by reviewing 49 research articles. The focus lies on the redefinition of nonprofits' mission and income streams, changing governance arrangements and shifting management practices. We find that, despite numerous detrimental effects cited in the literature, (a) generating commercial income can contribute to the financial stability of NPOs, and (b) hybridization towards the market domain can strengthen the organizational legitimacy of NPOs, suggesting that imitating for‐profit enterprises might contribute to nonprofit functioning in perception, rather than in practice.     

Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.     

Percentage points of the statistics for testing hypotheses on mean vectors of multivariate normal distributions with missing observations

A problem of testing of hypotheses on the mean vector of a multivariate normal distribution with unknown and positive definite covariance matrix is considered when a sample with a special, though not unusual, pattern of missing observations from that population is available. The approximate percentage points of the test statistic are obtained and their accuracy has been checked by comparing them with some exact percentage points which are calculated for complete samples and some special incomplete samples. The approximate percentage points are in good agreement with exact percentage points. The above work is extended to the problem of testing the hypothesis of equality of two mean vectors of two multivariate normal distributions with the same, unknown covariance matrix     

Economic and economic statistical designs for three-level control charts

In some situations, an appropriate quality measure uses three or more discrete levels to classify a product characteristic. For these situations, some control charts have been developed based on statistical criteria regardless of economic considerations. In this paper, we develop economic and economic statistical designs (ESD) for 3-level control charts. We apply the cost model proposed by Costa and Rahim.[Economic design of X charts with variable parameters: the Markov chain approach, J Appl Stat 28 (2001), 875–885] Furthermore, we assume that the length of time that the process remains in control is exponentially distributed which allows us to apply the Markov chain approach for developing the cost model. We apply a genetic algorithm to determine the optimal values of model parameters by minimizing the cost function. A numerical example is provided to illustrate the performance of the proposed models and to compare the cost of the pure economic and ESD for three-level control charts. A sensitivity analysis is also conducted in this numerical example.