Estimation of location extremes within general families of scale mixtures

In this paper, we study the estimation of the minimum and maximum location parameters, respectively, representing the minimum guaranteed lifetime of series and parallel systems of components, within a general class of scale mixtures. The conditional or underlying distribution has only the primary restriction of being a location-scale family with positive support. The mixing distribution is also quite general in that we only assume that it has positive support and finite second moment. For demonstrative purposes several special cases are highlighted such as the gamma, inverse-Gaussian, and discrete mixture. Various estimators, including bootstrap bias corrected estimators, are compared with respect to both mean-squared-error and Pitman's measure of closeness.     

基于SA和Bootstrap的LS-SVM参数优选及应用

文章针对最小二乘支持向量机的特点,通过Bootstrap建立适当的性能指标,用模拟退火算法(SA)优化最小二乘支持向量机的有关参数,并在非线性经济系统中应用.用最小二乘支持向量机对非线性经济系统进行预测的结果与神经网络预测的结果比较证明.该模型的预测精确度是令人满意的,文中提出的方法是可行的.     

Data tilting for time series

Summary. We develop a general methodology for tilting time series data. Attention is focused on a large class of regression problems, where errors are expressed through autoregressive processes. The class has a range of important applications and in the context of our work may be used to illustrate the application of tilting methods to interval estimation in regression, robust statistical inference and estimation subject to constraints. The method can be viewed as 'empirical likelihood with nuisance parameters'.     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.     

Role of informal sector recycling in waste management in developing countries

Many thousands of people in developing country cities depend on recycling materials from waste for their livelihoods. With the focus of the Millennium Development Goals on poverty reduction, and of waste strategies on improving recycling rates, one of the major challenges in solid waste management in developing countries is how best to work with this informal sector to improve their livelihoods, working conditions and efficiency in recycling.The general characteristics of informal recycling are reviewed, highlighting both positive and negative aspects. Despite the health and social problems associated with informal recycling, it provides significant economic benefits that need to be retained. Experience shows that it can be highly counterproductive to establish new formal waste recycling systems without taking into account informal systems that already exist. The preferred option is to integrate the informal sector into waste management planning, building on their practices and experience, while working to improve efficiency and the living and working conditions of those involved. Issues associated with integrating informal recycling into the formal waste management sector are discussed.     

低碳视角下农业集约化、绿色化与资源再生化 的实现机制研究

在实现"碳达峰碳中和"目标的重要历史机遇期,推动实现农业集约化、绿色化和资源再生化,构建资源节约型、绿色低碳型、生态循环型的农业发展模式,对于农业可持续发展具有重要意义。以2000-2018年我国31个省份为研究对象,通过面板向量自回归模型(PVAR),刻画资源消耗、农业产出、农业碳排放之间的动态传导机制。结果表明:(1)东部农业"碳达峰"节点出现较早,东北、西部相对较晚;2018年农业碳排放居前三的省份为湖南、黑龙江、河南,居后三的为北京、天津、上海;(2)资源消耗和农业产出之间呈现"低投入高产出"的农业集约化生产模式,但影响力微弱;农业产出和农业碳排放之间"高产出高排放"的情形长期面临农业绿色化的严峻考验;农业碳排放与资源消耗之间呈现"低排放低投入"的资源再生化现象,影响力短期微弱长期较强;(3)推动实现农业集约化、绿色化、资源再生化的关键在于探索降低农业碳排放的多重路径。因此,应强化农业集约化生产,充分发展资源再生化模式,探索形成农业绿色化格局新路径,以此来加快实现碳减排目标,推动农业可持续发展。     

Testing Inference in Inflated Beta Regressions under Model Misspecification

We consider testing inference in inflated beta regressions subject to model misspecification. In particular, quasi-z tests based on sandwich covariance matrix estimators are described and their finite sample behavior is investigated via Monte Carlo simulations. The numerical evidence shows that quasi-z testing inference can be considerably more accurate than inference made through the usual z tests, especially when there is model misspecification. Interval estimation is also considered. We also present an empirical application that uses real (not simulated) data.     

Bootstrapping estimators for the seemingly unrelated regressions model

In this paper we consider the possibility of using the bootstrap to estimate the finite sample variability of feasible generalized least squares and improved estimators applied to the seemingly unrelated regressions model. The improved estimators we employ include members of the Stein-rule family and a hierarchical Bayes estimator proposed by Blattberg and George (1991). Simulation experiments are carried out using several SUR examples as well as a very large example based on the price-promotion model, and data, from marketing research.     

Resampling-based Classification Using Depth for Functional Curves

The depths, which have been used to detect outliers or to extract a representative subset, can be applied to classification. We propose a resampling-based classification method based on the fact that resampling techniques yield a consistent estimator of the distribution of a statistic. The performance of this method was evaluated with eight contaminated models in terms of Correct Classification Rates (CCRs), and the results were compared with other known methods. The proposed method consistently showed higher average CCRs and 4% higher CCR at the maximum compared to other methods. In addition, this method was applied to Berkeley data. The average CCRs were between 0.79 and 0.85.     

A Comparative Study of Model-based Tests of Independence for Ordinal Data Using the Bootstrap

When analyzing categorical data using loglinear models in sparse contingency tables, asymptotic results may fail. In this paper the empirical properties of three commonly used asymptotic tests of independence, based on the uniform association model for ordinal data, are investigated by means of Monte Carlo simulation. Five different bootstrapped tests of independence are presented and compared to the asymptotic tests. The comparisons are made with respect to both size and power properties of the tests. Results indicate that the asymptotic tests have poor size control. The test based on the estimated association parameter is severely conservative and the two chi-squared tests (Pearson, likelihood-ratio) are both liberal. The bootstrap tests that either use a parametric assumption or are based on non-pivotal test statistics do not perform better than the asymptotic tests in all situations. The bootstrap tests that are based on approximately pivotal statistics provide both adjustment of size and enhancement of power. These tests are therefore recommended for use in situations similar to those included in the simulation study.