A Similarity Measure Based on Species Proportions

ABSTRACT

There are several indices for measuring the similarity of two populations, including the ratio of the number of shared species to the number of distinct species (Jaccard's index) and the conditional probability of observing a shared species (Smith et al., 1996 Smith , W. , Solow , A. R. , Preston , P. E. ( 1996 ). An estimator of species overlap using a modified beta-binomial model. Biometrics 52 : 1472 – 1477 . [CSA] [CROSSREF] [Crossref], [Web of Science ®] , [Google Scholar]). However, these indices only take into account the number of species and species proportions of shared species. In this article, we propose a new similarity index which includes the species proportions of both the shared and non shared species in each population, and also propose a Nonparametric Maximum Likelihood Estimator (NPMLE) for this index. Bootstrap and delta methods are used to evaluate the standard errors of the NPMLE. Based on a loss function, we also compare a class of nonparametric estimators for the proposed index in various situations.     

Estimation of Laspeyres Price Indexes Using the Prediction Approach for Finite Population Sampling

Estimators of chain and fixed-base Laspeyres price indexes are studied using the prediction approach to finite population sampling. The estimators include some that are based on those used in several U.S. government index programs and others derived from prediction models. Biases and variances of the estimators are studied for a case in which the reference period index weights are unknown for nonsample items. Under a model for a one-period price change in which items have common within-stratum means, unbiased estimators can be constructed, but under a more general regression model, special sample balance conditions are needed for unbiasedness of those estimators. The theory for the estimators of fixed-base indexes is illustrated in an empirical study using a population of items priced for the U.S. Consumer Price Index.     

Some Observations,a Suggestion,and Some Comments on the Conway-Roberts Article

This article provides new tools for the evaluation of dynamic stochastic general equilibrium (DSGE) models and applies them to a large-scale new Keynesian model. We approximate the DSGE model by a vector autoregression, and then systematically relax the implied cross-equation restrictions and document how the model fit changes. We also compare the DSGE model's impulse responses to structural shocks with those obtained after relaxing its restrictions. We find that the degree of misspecification in this large-scale DSGE model is no longer so large as to prevent its use in day-to-day policy analysis, yet is not small enough to be ignored.     

The Implications of Using Messy Data to Estimate Production-Frontier-Based Technical Efficiency Measures

An empirical study of efficiency at the plant level, requiring production and financial data, was done using frontier function specifications. It is not evident from the implementation of the production-frontier models that different methodologies will consistently flag the same observations as being efficient or inefficient. As a result, outlier diagnostics for individual observations and for subsets of observations are used to achieve a relative index of influentiality within the spectrum of efficiency. These outlier diagnostic tests consistently flag the same subset of efficient and inefficient observations as the frontier models and additionally clarify ranking discrepancies among the frontier model specifications.     

西部地区物流实力综合评价实证分析

通过构建评价物流实力的指标体系,选取15个与物流业相关的具有代表性的评价指标作为西部十省(市)区的物流实力综合评价的原始指标,利用改进的主成分分析法对15个指标数据进行处理分析,对西部十省(市)区物流实力给出了客观评价,并指出了主要的影响指标,同时就物流业进一步发展提出了积极、合理的建议。     

发达经济体与新兴经济体竞争力比较——基于全球竞争力指数视角

在经济全球化的今天,发达经济体与新兴经济体之间的竞争日益激烈.首先,选取30个发达经济体和29个新兴经济体的基本要素指标、效率因素指标和创新因素指标,对发达经济体与新兴经济体竞争力孰强孰弱这一问题进行研究.其次,通过对各指标的计算和比较,得出新兴经济体竞争力仍比较弱的结论.最后,提出新兴经济体要想提升自身竞争力必须从政治制度、宏观经济运行、教育发展、基础设施建设等方面进行改进和完善的政策建议.     

基于改进D—S证据理论的TOPSIS模型在科技奖励评价中的应用

针对科技奖励评价的特点,根据改进D—S证据合成规则,将专家的评价指标值转化为指标的综合得分并形成决策矩阵;结合TOPSIS模型求解理想解和负理想解,计算距离和贴近度,对各评价项目进行综合排名。实证结果表明：该模型能够很好地解决科技奖励评价过程中的不确定性问题,为科技奖励综合评价提供了一种新的思路。     

Estimating Process Capability Index C PM Using a Bootstrap Sequential Sampling Procedure

Construction of a confidence interval for process capability index C _PM is often based on a normal approximation with fixed sample size. In this article, we describe a different approach in constructing a fixed-width confidence interval for process capability index C _PM with a preassigned accuracy by using a combination of bootstrap and sequential sampling schemes. The optimal sample size required to achieve a preassigned confidence level is obtained using both two-stage and modified two-stage sequential procedures. The procedure developed is also validated using an extensive simulation study.     

Parameter Estimation of Stable Distributions

ABSTRACT

In finance, economics, statistical physics, signal processing, telecommunications, etc., we frequently meet data sets with outliers that transport important information. α-stable distributions are found more suitable in modeling these kind of data. But the lack of simple and effective methods of estimating their parameters limited their applications to wider variety of fields. In this article we develop an unbiased estimator for the stable index α. With the structure of U-statistic, it inherits all the good statistical properties from U-statistics. A consistent estimator of its asymptotic variance is provided. The asymptotic normality of the given estimator holds when using the estimated variance for standardization. Simulation studies are performed. The results support our theory.     

A note on estimation in bernoulli trials with dependence

Finite sample properties of estimators for the parameters of a dependent Bernoulli process are investigated using Monte Carlo techniques. A ratio estimator is proposed for the dependence parameter of the model and is compared to the approximate maximum likelihood estimator given by Klotz. It is shown that both estimators have a downward bias that is extreme in certain cases and that samples well in excess of 200 may be necessary before the asymptotic theory can be applied.