Comparison of test vs. control treatments using distance optimality criterion

We consider the problem of comparison of one test treatment (τ₀) with a set of v control treatments (τ₁, τ₂, …, τ_v) using distance optimality [DS-optimality] criterion introduced by Sinha (1970) in some treatment-connected design settings. It turns out that the nature of DS-optimal designs is quite similar to that for the usual A−, D− and E− optimality criteria. However, the optimality problem is quite complicated in most situations. First we deal with the CRD model and derive DS-optimal allocations for a given set of treatments. The results are almost identical to the A-optimal allocations for such problems. Then we consider a block design set-up and examine the nature of DS-optimal designs. In the process, we introduce the method of weighted coverage probability and maximize the resulting expression to obtain an optimal design. Received: December 1999     

Locally Most Powerful and Other Rank Tests for Independence – with a Contaminated Weighted Alternative

Several authors in the literature have attempted the quantification of the concept of stochastic dependence for bivariate distribution. Two weighted rank tests for testing independence against a weighted contamination alternative is proposed and their distributional properties are studied. We also derived a locally most powerful rank test for the alternative setting. The rank tests proposed are shown to be asymptotic locally most powerful for specific distributions.     

混合地理加权回归模型中的空间相关性检验和参数估计研究

对混合地理加权回归模型,提出新的空间相关性检验统计量,利用三阶矩?2逼近方法导出了其检验p-值的近似计算公式,模拟结果显示该检验统计量在检测空间相关性方面具有满意的功效。为了处理数据中可能同时存在的空间相关性和空间异质性,引入一类新的混合地理加权空间滞后回归模型,模拟结果表明该估计方法具有较高的可靠性和稳健性,与全局空间滞后回归模型比较,混合地理加权空间滞后回归模型在处理空间异质性方面具有更优良的表现。     

Optimal comparison of misspecified moment restriction models under a chosen measure of fit

Suppose that the econometrician is interested in comparing two misspecified moment restriction models, where the comparison is performed in terms of some chosen measure of fit. This paper is concerned with describing an optimal test of the Vuong (1989) and Rivers and Vuong (2002) type null hypothesis that the two models are equivalent under the given measure of fit (the ranking may vary for different measures). We adopt the generalized Neyman–Pearson optimality criterion, which focuses on the decay rates of the type I and II error probabilities under fixed non-local alternatives, and derive an optimal but practically infeasible test. Then, as an illustration, by considering the model comparison hypothesis defined by the weighted Euclidean norm of moment restrictions, we propose a feasible approximate test statistic to the optimal one and study its asymptotic properties. Local power properties, one-sided test, and comparison under the generalized empirical likelihood-based measure of fit are also investigated. A simulation study illustrates that our approximate test is more powerful than the Rivers–Vuong test.     

Envy and Habits: Panel Data Estimates of Interdependent Preferences

We estimate the importance of preference interdependence from consumption choices. Our strategy follows the literature that tests the constraints imposed by optimality on the evolution of individual consumption. The introduction of habits and envy places additional restrictions on the evolution of the optimal consumption path. We use a unique data set to test these restrictions. Our estimates suggest that, if one defines utility over consumption services, a large fraction of these services is relative, with one third of the weight placed in the consumption of the reference group and another third placed in the agent's past consumption.     

A Foundational Justification for a Weighted Likelihood Approach to Inference

Two types of probability are discussed, one of which is additive whilst the other is non-additive. Popular theories that attempt to justify the importance of the additivity of probability are then critically reviewed. By making assumptions the two types of probability put forward are utilised to justify a method of inference which involves betting preferences being revised in light of the data. This method of inference can be viewed as a justification for a weighted likelihood approach to inference where the plausibility of different values of a parameter θ based on the data is measured by the quantity q (θ) = l ( , θ) w (θ), where l ( , θ) is the likelihood function and w (θ) is a weight function. Even though, unlike Bayesian inference, the method has the disadvantageous property that the measure q (θ) is generally non-additive, it is argued that the method has other properties which may be considered very desirable and which have the potential to imply that when everything is taken into account, the method is a serious alternative to the Bayesian approach in many situations. The methodology that is developed is applied to both a toy example and a real example.     

Optimality results on orthogonal arrays plus <Emphasis Type="Italic">p</Emphasis> runs for <Emphasis Type="Italic">s</Emphasis><Superscript><Emphasis Type="Italic">m</Emphasis></Superscript> factorial experiments

The optimality of designs obtained by adding p runs to an orthogonal array is studied for experiments involving m factors each at s levels. The optimality criterion used here, is the Type 1 criterion due to Cheng (1978) which is an extension of Kiefer (1975) universal optimality criterion. Unlike what happens with orthogonal array plus one run designs, the behavior of designs obtained via augmentation of an orthogonal array by p runs depends on the particular runs added.     

Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

基于改进的加权贝叶斯分类算法在空间数据中的应用

朴素贝叶斯算法是一种简单而高效的分类算法,但它的属性独立性假设,影响了它的分类性能。针对这个问题,提出一种基于属性约简的PLS加权朴素贝叶斯分类算法。该算法首先分析属性之间的相关性,通过属性约简选择一组近似独立的属性约简子集,提出改进的偏最小二乘回归加权朴素贝叶斯分类算法,实验结果表明,改进算法具有较高的分类准确度。并将改进的算法应用于边坡识别问题中。     

Hodges–Lehmann optimality for testing moment conditions

This paper studies the Hodges and Lehmann (1956) optimality of tests in a general setup. The tests are compared by the exponential rates of growth to one of the power functions evaluated at a fixed alternative while keeping the asymptotic sizes bounded by some constant. We present two sets of sufficient conditions for a test to be Hodges–Lehmann optimal. These new conditions extend the scope of the Hodges–Lehmann optimality analysis to setups that cannot be covered by other conditions in the literature. The general result is illustrated by our applications of interest: testing for moment conditions and overidentifying restrictions. In particular, we show that (i) the empirical likelihood test does not necessarily satisfy existing conditions for optimality but does satisfy our new conditions; and (ii) the generalized method of moments (GMM) test and the generalized empirical likelihood (GEL) tests are Hodges–Lehmann optimal under mild primitive conditions. These results support the belief that the Hodges–Lehmann optimality is a weak asymptotic requirement.     

Weakly balanced contributions and the weighted Shapley values

We provide a concise characterization of the class of positively weighted Shapley values by three properties, two standard properties, efficiency and marginality, and a relaxation of the balanced contributions property called the weak balanced contributions property. Balanced contributions: the amount one player gains or loses when another player leaves the game equals the amount the latter player gains or loses when the former player leaves the game. Weakly balanced contributions: the direction (sign) of the change of one player’s payoff when another player leaves the game equals the direction (sign) of the change of the latter player’s payoff when the former player leaves the game. Given this characterization, the symmetric Shapley value can be “extracted”from the class of positively weighted Shapley values by either replacing the weak balanced contributions property with the standard symmetry property or by strengthening the former into the balanced contributions property.     

Estimation in Varying-coefficient Proportional Hazard Regression Model

In this paper, varying coefficient proportional hazard regression models are considered. The model is an important extension of the Cox model, and arises naturally if the coefficients change over different groups characterized by certain covariates in practice. Under random censorship, weighted partial likelihood estimators are defined for the varying coefficients by maximizing weighted partial likelihoods. It is shown that the proposed estimators are consistent and asymptotically normal.     

Cointegration and control: Assessing the impact of events using time series data

Control groups can provide counterfactual evidence for assessing the impact of an event or policy change on a target variable. We argue that fitting a multivariate time series model offers potential gains over a direct comparison between the target and a weighted average of controls. More importantly, it highlights the assumptions underlying methods such as difference in differences and synthetic control, suggesting ways to test these assumptions. Gains from simple and transparent time series models are analysed using examples from the literature, including the California smoking law of 1989 and German reunification. We argue that selecting controls using a time series strategy is preferable to existing data‐driven regression methods.     

Axiomatization of weighted (separable) utility

Nontrivial decision problems typically involve a trade-off among multiple attributes of choice options. One simple way of resolving such trade-offs is to aggregate multiple attributes into one real-valued index, known as weighted or separable utility. Applications of weighted utility can be found in choice under risk (expected utility) and uncertainty (subjective expected utility), intertemporal choice (discounted utility) and welfare economics (utilitarian social welfare function). This paper presents an alternative behavioral characterization (preference axiomatization) of weighted utility. It is shown that necessary and sufficient conditions for weighted utility are completeness, continuity, bi-separable transitivity (and transitivity if none of the attributes is null, or inessential).     

Strong laws for weighted sums of NA random variables

Strong laws are established for linear statistics that are weighted sums of an negatively associated (NA) random sample. The results obtained not only generalize the results of Sung (Stat. Probab. Lett. 52:413–419, 2001) to NA random variables, but also extend and sharpen them. Research supported by Youth Talent Foundation of Zhejiang Gongshang University (Q07-07).     

Response adaptive procedures with dual optimality

The paper proposes an optimal response-adaptive procedure for a general class of responses using a combination of two clinically relevant optimality criteria. We provide a thorough development for trials involving two treatments and sketch the possible extension for multiple treatments. Some related asymptotic results are worked out. We provide simulation studies to compare the performance of the proposed procedure with some of the existing competitors. We illustrate our methodology on data from a real clinical trial.     

Nonparametric Methods for Evaluating Economic Efficiency and Imperfect Competition

This article unifies and extends ideas from nonparametric production analysis and DEA for testing organizational efficiency. We show how the admissible price set can be restricted to account for prior information on prices. These restrictions may relate prices to input and output quantities in order to test noncompetitive behavior of the evaluated decision making unit. While the resulting efficiency tests cannot always be cast into linear programming problems, we discuss various solution strategies for the tests. Thereby we consider the question when does local optimality of the result guarantee global optimality. We also show how the decision maker's preferences, for example ranking information, can be adopted into DEA models in a simple manner. Finally, the approach with price restrictions is illustrated with an application to test noncompetitive behavior of the pulp and paper industries in Finland.     

Universally optimal balanced changeover designs with first residuals

Considering the presence of first order residual effects of treatments, a family of variance balanced changeover designs has been presented and universal optimality of the designs is established. The designs use only v experimental units and (v ? 1)/2 periods for v = 4t + 3 prime or prime power number of treatments; t being a positive integer. A special feature of the proposed designs is that ‘in the order of presentation of treatments to experimental units over periods, each treatment is once immediately preceded by only half of the other treatments and is immediately followed once by the remaining half of the treatments’. This characteristic results in reducing the size of the variance balanced designs considerably.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

码头间集装箱拖箱业务调度系统研究

分析同一港口集装箱码头间拖箱业务产生原因的基础上,根据上海港（案例港）的实地调研数据,采用Dijkstra算法和模糊综合评判法,建立码头间集装箱拖箱业务调度模型及调度系统。用C＋＋11语言,编写了适用于港口的数字模拟平台,通过仿真,验证了设计的新调度模型比传统人工方式更有效率,为港口运营提供了切实可行的系统支持。