Integrated nested Laplace approximation for the analysis of count data via the combined model: A simulation study

The combined model accounts for different forms of extra-variability and has traditionally been applied in the likelihood framework, or in the Bayesian setting via Markov chain Monte Carlo. In this article, integrated nested Laplace approximation is investigated as an alternative estimation method for the combined model for count data, and compared with the former estimation techniques. Longitudinal, spatial, and multi-hierarchical data scenarios are investigated in three case studies as well as a simulation study. As a conclusion, integrated nested Laplace approximation provides fast and precise estimation, while avoiding convergence problems often seen when using Markov chain Monte Carlo.     

Room for manoeuvre: User participation in water resources management in Burkina Faso

Participation in natural resources management is widely promoted in sub‐Saharan Africa, but faces mounting criticism from social science scholars who rarely engage with it in practice. We use the notion of room for manoeuvre to reflect on a multi‐level participatory approach designed to support the Burkinabè Integrated Water Resources Management policy and propose ways of engaging constructively with local users and policy‐makers. Within an “invited space” of participation, water users’ room for manoeuvre was enhanced through the acquisition of new knowledge on the legal Integrated Water Resources Management (IWRM) framework. This allowed them to interact with decision‐makers and to extend their networks. Power imbalances were discussed, but this did not lead to modifying existing power structures that hinge on broader societal dynamics.     

Nonparametric density deconvolution by weighted kernel estimators

Nonparametric density estimation in the presence of measurement error is considered. The usual kernel deconvolution estimator seeks to account for the contamination in the data by employing a modified kernel. In this paper a new approach based on a weighted kernel density estimator is proposed. Theoretical motivation is provided by the existence of a weight vector that perfectly counteracts the bias in density estimation without generating an excessive increase in variance. In practice a data driven method of weight selection is required. Our strategy is to minimize the discrepancy between a standard kernel estimate from the contaminated data on the one hand, and the convolution of the weighted deconvolution estimate with the measurement error density on the other hand. We consider a direct implementation of this approach, in which the weights are optimized subject to sum and non-negativity constraints, and a regularized version in which the objective function includes a ridge-type penalty. Numerical tests suggest that the weighted kernel estimation can lead to tangible improvements in performance over the usual kernel deconvolution estimator. Furthermore, weighted kernel estimates are free from the problem of negative estimation in the tails that can occur when using modified kernels. The weighted kernel approach generalizes to the case of multivariate deconvolution density estimation in a very straightforward manner.     

青岛一套表的实践与经验

 企业统计一套表一直是统计制度方法改革和实践中的焦点问题。本文通过对青岛市统计局企业一套表制度实施情况的案例分析,系统界定了企业一套表的概念和内涵,全面展现了企业一套表的运作过程,客观分析了制约企业一套表实施的主要原因,并提出了在现阶段实施企业统计一套表的条件和要求。     

房地产预警指标体系及综合预警方法研究

 本文在对常用的房地产预警指标体系选择方法及筛选流程进行分析的基础上,提出了一种主、客观相结合的房地产预警指标选择方法,即先采用综合分析方法对指标进行初次选择,然后用聚类分析和相关分析相结合的方法进行再次选择。最后建立了武汉市房地产预警指标系统,并进行了房地产综合预警。     

地方利益、区域经济一体化合作与福祉

地方利益包括地方政府官员的利益与地方公利,其中,地方政府官员利益居于核心层并发挥基础性、关键性作用.地方政府官员的利益又包括物质利益与非物质利益,非物质利益中的政治利益至关重要.地方利益引致地方政府行为变异,导致区域经济不合作,进而造成福祉损失.只有从地方利益入手,准确清晰地界定并规范和约束地方利益,并进行相应的制度创新,才能真正推动我国区域经济一体化合作,增进福祉.     

Bayesian Analysis in Regression Models Using Pseudo-Likelihoods

This article deals with the issue of using a suitable pseudo-likelihood, instead of an integrated likelihood, when performing Bayesian inference about a scalar parameter of interest in the presence of nuisance parameters. The proposed approach has the advantages of avoiding the elicitation on the nuisance parameters and the computation of multidimensional integrals. Moreover, it is particularly useful when it is difficult, or even impractical, to write the full likelihood function.

We focus on Bayesian inference about a scalar regression coefficient in various regression models. First, in the context of non-normal regression-scale models, we give a theroetical result showing that there is no loss of information about the parameter of interest when using a posterior distribution derived from a pseudo-likelihood instead of the correct posterior distribution. Second, we present non trivial applications with high-dimensional, or even infinite-dimensional, nuisance parameters in the context of nonlinear normal heteroscedastic regression models, and of models for binary outcomes and count data, accounting also for possibile overdispersion. In all these situtations, we show that non Bayesian methods for eliminating nuisance parameters can be usefully incorporated into a one-parameter Bayesian analysis.     

Implementation of JIT purchasing: An integrated approach

This article addresses the necessity of integration between buyer and supplier for effective implementation of the JIT system. An integrated lot-splitting model of facilitating multiple shipments in small lots is developed and compared with the existing approach in a simple JIT environment, single-buyer-single-supplier, under deterministic conditions for a single product. It is shown that the optimal policy adopted by the integrated approach can provide a strong and consistent cost-minimizing effect for both buyer and supplier over the existing approach.     

A case study of the impact of integrated project governances on PPP project performance

Under the new normal state, the PPP project will play a more and more important role in the social and economic development of China. To improve the performance of PPP project management, it is necessary to implement integrated project governances. Firstly, according to the index system of two kinds of PPP projects governances (Contract Governance and Relationship Governance) and PPP project management performance determined by theoretical analysis, the DDX project is selected as the analysis object. After identifying the case, this paper explains the basic information and preliminary work of the case. Then, the three contents of contract governance, relationship governance and project performance are analyzed comprehensively. Case studies show that all of these two governance modes have positive effects on project management performance. However, due to the lack of information in the case, the validity of the conclusion also needs to be verified again.     

Recent and classical goodness-of-fit tests for the Poisson distribution

We give a critical synopsis of classical and recent tests for Poissonity, our emphasis being on procedures which are consistent against general alternatives. Two classes of weighted Cramér–von Mises type test statistics, based on the empirical probability generating function process, are studied in more detail. Both of them generalize already known test statistics by introducing a weighting parameter, thus providing more flexibility with regard to power against specific alternatives. In both cases, we prove convergence in distribution of the statistics under the null hypothesis in the setting of a triangular array of rowwise independent and identically distributed random variables as well as consistency of the corresponding test against general alternatives. Therefore, a sound theoretical basis is provided for the parametric bootstrap procedure, which is applied to obtain critical values in a large-scale simulation study. Each of the tests considered in this study, when implemented via the parametric bootstrap method, maintains a nominal level of significance very closely, even for small sample sizes. The procedures are applied to four well-known data sets.