Evaluation of strategies for Downs Syndrome screening

Downs Syndrome is a chromosomal disorder affecting approximately 1 in 700 live births in unscreened populations. Definitive prenatal diagnostic tests are available but they are invasive and can cause miscarriages. Non-invasive tests earlier in pregnancy have the potential for identifying pregnancies that are at sufficient risk to warrant the invasive diagnostic test being performed. A model has been developed to evaluate possible screening strategies. Although at first sight this problem seems amenable to traditional decision analysis, our alternative method has proved more fruitful. The method can be used to derive closed form analytical expressions for a number of relevant outcome measures. This modelling allows the study of the effect of the timings of the two tests within pregnancy, optimisation of screening options and investigation of effects related to diagnostic accuracy.     

半参数广义线性随机效应模型的影响分析

该文系统研究了半参数广义线性随机效应模型的统计诊断与影响分析方法, 证明了数据删除模型和均值漂移模型的等价性定理, 给出了广义Cook距离等诊断统计量及异常点的Score检验统计量并研究了该模型的局部影响分析,分别对加权扰动模型, 响应变量扰动模型得到了影响距阵的计算公式, 最后通过一个实例验证了文中给出诊断方法的有效性.     

Testing for Varying Dispersion in Exponential Family Nonlinear Models

A diagnostic model and several new diagnostic statistics are proposed for testing for varying dispersion in exponential family nonlinear models. A score statistic and an adjusted score statistic based on Cox and Reid (1987, J. Roy. Statist. Soc. Ser. B, 55, 467-471) are derived in normal, inverse Gaussian, and gamma nonlinear models. An adjusted likelihood ratio statistic is also given for normal and inverse Gaussian nonlinear models. The results of simulation studies are presented, which show that the adjusted tests keep their sizes better and are more powerful than the ordinary tests.     

半参数广义线性模型的影响分析与异常点检验

统计诊断就是对统计推断方法解决问题的全过程进行诊断，而影响分析是统计诊断中十分重要的分支．本文针对半参数广义线性模型，证明了数据删除模型和均值漂移模型的等价性定理，给出了诸如广义Cook距离等诊断统计量并研究了异常点的Score检验统计量，最后通过实例验证了本文给出的诊断方法的有效性。     

三层供应链上需求信息不对称下Newsboy型协作问题

本文主要研究单产品在单周期内由供应商、制造商、零售商组成的三层供应链上的协作订购问题,即在随机需求下供应商、制造商、零售商以利润最大化为目的的最优协作订购问题。在需求信息不对称下,零售商充分了解需求信息。在协作订购时面临四种策略,给出了在这四种策略下的四种利润模型及零售商在这四种策略下的最优订购量并比较它们的大小,最后通过需求服从正态分布的实例验证了供应商一制造商一零售商在采用数量折扣和返回措施三者完全合作时供应链上的利润最大。     

Validation of association

Recognizing, quantifying and visualizing associations between two variables is increasingly important. This paper investigates how a new function-valued measure of dependence, the quantile dependence function, can be used to construct tests for independence and to provide an easily interpretable diagnostic plot of existing departures from the null model. The dependence function is designed to detect general dependence structure between variables in quantiles of the joint distribution. It gives an insight into how the dependence structure changes in different parts of the joint distribution. We define new estimators of the dependence function, discuss some of their properties, and apply them to construct new tests of independence. Numerical evidence is given to the tests benefits against three recognized independence tests introduced in the previous years. In real-data analysis, we offer the use of our tests and the graphical presentation of the underlying dependence structure.     

A tabu search heuristic for the split delivery vehicle routing problem with production and demand calendars

The purpose of this article is to propose a tabu search heuristic for the split delivery Vehicle Routing Problem with Production and Demand Calendars (VRPPDC). This new problem consists of determining which customers will be served by a common carrier, as well as the delivery routes for those served by the private fleet, in order to minimize the overall transportation and inventory costs. We first model this problem and then propose a simple decomposition procedure that can be used to provide a starting solution. Next, we introduce a new tabu search heuristic and we describe two new neighbor reduction strategies. Finally, we present the results of our extensive computational tests. According to these tests, our reduction strategies are efficient not only at reducing computing time but also at improving the overall solution quality.     

A stochastic programming model for asset liability management of a Finnish pension company

This paper describes a stochastic programming model that was developed for asset liability management of a Finnish pension insurance company. In many respects the model resembles those presented in the literature, but it has some unique features stemming from the statutory restrictions for Finnish pension insurance companies. Particular attention is paid to modeling the stochastic factors, numerical solution of the resulting optimization problem and evaluation of the solution. Out-of-sample tests clearly favor the strategies suggested by our model over static fixed-mix and dynamic portfolio insurance strategies. Financial support from the Foundation for the Helsinki School of Economics under grants number 9981114 and 9981117 for P. Hilli and M. Koivu is gratefully acknowledged. The work of T. Pennanen was supported by Finnish Academy under contract no. 3385     

Top-predator interference and gestation delay as determinants of the dynamics of a realistic model food chain

An attempt has been made to understand the role of top predator interference and gestation delay on the dynamics of a three species food chain model involving intermediate and top predator populations. Interaction between the prey and an intermediate predator follows the Volterra scheme (with Holling type IV functional response), while that between the top predator and its prey depends on Beddington–DeAngelis type functional response. Stability switches and Hopf-bifurcation occurs when the delay crosses some critical value. Model system exhibits irregular behavior when the interference is high or gestation period is larger than its critical value. Furthermore, the direction of Hopf-bifurcation and the stability of the bifurcating periodic solutions are determined using the center manifold theorem and normal form theory. Computer simulations have been carried out to illustrate the analytical findings. Different diagnostic tests, like, initial sensitivity, Lyapunov exponent, recurrence plot tests ensure the complex dynamical behavior of the model system. Finally, we observed the subcritical Hopf-bifurcation phenomena in the designed model system and the bifurcating periodic solution is unstable for the considered set of parameter values.     

Optimal strategies to diminish a pest population via bilinear controls

In this work we model and analyze two control strategies to diminish a pest population using traps. The action of any trap depends on its age. Both problems contain bilinear control rates. The large-time behavior of the model with time-periodic inflow is investigated. The first control strategy deals with a finite horizon problem while the second one is related to a time-periodic problem. We obtain Pontryagin’s principle for both control problems. A special attention is given to the periodic problem. Pontryagin’s principle is used to derive a conceptual gradient-type algorithm to approximate the optimal solution. Numerical tests are given.     

Improved threshold diagnostic plots for extreme value analyses

A crucial aspect of threshold-based extreme value analyses is the level at which the threshold is set. For a suitably high threshold asymptotic theory suggests that threshold excesses may be modelled by a generalized Pareto distribution. A common threshold diagnostic is a plot of estimates of the generalized Pareto shape parameter over a range of thresholds. The aim is to select the lowest threshold above which the estimates are judged to be approximately constant, taking into account sampling variability summarized by pointwise confidence intervals. This approach doesn’t test directly the hypothesis that the underlying shape parameter is constant above a given threshold, but requires the user subjectively to combine information from many dependent estimates and confidence intervals. We develop tests of this hypothesis based on a multiple-threshold penultimate model that generalizes a two-threshold model proposed recently. One variant uses only the model fits from the traditional parameter stability plot. This is particularly beneficial when many datasets are analysed and enables assessment of the properties of the test on simulated data. We assess and illustrate these tests on river flow rate data and 72 series of significant wave heights.     

Optimal testing strategies in overlapped design process

Testing is an important activity in product development. Past studies, which are developed to determine the optimal scheduling of tests, often focused on single-stage testing of sequential design process. This paper presents an analytical model for the scheduling of tests in overlapped design process, where a downstream stage starts before the completion of upstream testing. We derive optimal stopping rules for upstream and downstream stages’ testing, together with the optimal time elapsed between beginning the upstream tests and beginning the downstream development. We find that the cost function is first convex then concave increasing with respect to upstream testing duration. A one-dimensional search algorithm is then proposed for finding the unique optimum that minimizes the overall cost. Moreover, the impact of different model parameters, such as the problem-solving capacity and opportunity cost, on the optimal solution is discussed. Finally, we compare the testing strategies in overlapped process with those in sequential process, and get some additional results. The methodology is illustrated with a case study at a handset design company.     

Solution approaches for the soft drink integrated production lot sizing and scheduling problem

In this paper we present a mixed integer programming model that integrates production lot sizing and scheduling decisions of beverage plants with sequence-dependent setup costs and times. The model considers that the industrial process produces soft drink bottles in different flavours and sizes, and it is carried out in two production stages: liquid preparation (stage I) and bottling (stage II). The model also takes into account that the production bottleneck may alternate between stages I and II, and a synchronisation of the production between these stages is required. A relaxation approach and several strategies of the relax-and-fix heuristic are proposed to solve the model. Computational tests with instances generated based on real data from a Brazilian soft drink plant are also presented. The results show that the solution approaches are capable of producing better solutions than those used by the company.     

An overview and framework for PD backtesting and benchmarking

In order to manage model risk, financial institutions need to set up validation processes so as to monitor the quality of the models on an ongoing basis. Validation can be considered from both a quantitative and qualitative point of view. Backtesting and benchmarking are key quantitative validation tools, and the focus of this paper. In backtesting, the predicted risk measurements (PD, LGD, EAD) will be contrasted with observed measurements using a workbench of available test statistics to evaluate the calibration, discrimination and stability of the model. A timely detection of reduced performance is crucial since it directly impacts profitability and risk management strategies. The aim of benchmarking is to compare internal risk measurements with external risk measurements so as to better gauge the quality of the internal rating system. This paper will focus on the quantitative PD validation process within a Basel II context. We will set forth a traffic light indicator approach that employs all relevant statistical tests to quantitatively validate the used PD model, and document this approach with a real-life case study. The set forth methodology and tests are the summary of the authors’ statistical expertise and experience of world-wide observed business practices.     

Likelihood ratio tests for equality of shape under varying degrees of orientation invariance

We consider a problem from image cytometry where the objective is to describe possible changes in the shape and orientation of cellular nuclei after treatment with a toxin. The shapes of nuclei are represented by individual ellipses. It is argued that the shape comparison problem can be formulated as a generalization of a hypothesis test for the equality of covariance matrices. For many cell types, the test statistic should be invariant with respect to orientations of the cells. For other cell types, the test statistic should be equivariant with respect to orientations of the cells, but invariant with respect to orientations of the images. Likelihood ratio tests (LRTs) are derived under a Wishart model. The likelihood maximization uses a new result about the minimization of the determinant of a sum of matrices under individual rotations. The applicability and limitations of these LRTs are demonstrated by means of simulation experiments. The reference distributions of the test statistics under the null hypothesis are obtained using unrestricted and restricted randomization procedures. Justification for the Wishart model is provided using a residual diagnostic method. The scientific implications of the results are considered.     

Optimal sequential inspection policies

We consider the problem of combining a given set of diagnostic tests into an inspection system to classify items of interest (cases) with maximum accuracy such that the cost of performing the tests does not exceed a given budget constraint. One motivating application is sequencing diagnostic tests for container inspection, where the diagnostic tests may correspond to radiation sensors, document checks, or imaging systems. We consider mixtures of decision trees as inspection systems following the work of Boros et al. (Nav. Res. Logist. 56:404?C420, 2009). We establish some properties of efficient inspection systems and characterize the optimal classification of cases, based on some of their test scores. The measure of performance is the fraction of all cases in a specific class of interest, which are classified correctly. We propose a dynamic programming algorithm that constructs more complex policies by iteratively prefixing devices to a subset of policies and thereby enumerating all of the efficient (i.e., undominated) inspection policies in the two dimensional cost-detection space. Our inspection policies may sequence an arbitrary number of tests and are not restricted in the branching factor. Our approach directly solves the bi-criterion optimization problem of maximizing detection and minimizing cost, and thus supports sensitivity analysis over a wide range of budget and detection requirements.     

Empirical likelihood ratio tests for multivariate regression models

This paper proposes some diagnostic tools for checking the adequacy of multivariate regression models including classical regression and time series autoregression. In statistical inference, the empirical likelihood ratio method has been well known to be a powerful tool for constructing test and confidence region. For model checking, however, the naive empirical likelihood (EL) based tests are not of Wilks’ phenomenon. Hence, we make use of bias correction to construct the EL-based score tests and derive a nonparametric version of Wilks’ theorem. Moreover, by the advantages of both the EL and score test method, the EL-based score tests share many desirable features as follows: They are self-scale invariant and can detect the alternatives that converge to the null at rate n ^−1/2, the possibly fastest rate for lack-of-fit testing; they involve weight functions, which provides us with the flexibility to choose scores for improving power performance, especially under directional alternatives. Furthermore, when the alternatives are not directional, we construct asymptotically distribution-free maximin tests for a large class of possible alternatives. A simulation study is carried out and an application for a real dataset is analyzed.      

An empirical study on the Lanchester model of combat for competitive advertising decisions

This paper presents an empirical study on the Lanchester model of combat for competitive advertising decisions. Three issues are evaluated: (i) the specification of the market share response model; (ii) the effect of inflation on the estimation of the response model; and (iii) the performance of competitive strategies. It is shown that (a) the square root function that is used in previous studies is often inappropriate to characterize the market share response model; (b) market share variations are more responsive to current advertising expenditures; (c) closed-loop Nash equilibrium strategies are better competitive advertising strategies for firms to maximize profits than open-loop Nash equilibrium strategies; and (d), finally, general perfect equilibria Nash equilibrium strategies developed by Case are usually not good competitive advertising strategies for firms to maximize profits.     

企业联盟发展的力学分析与联盟策略

企业联盟能通过资源共享促进企业可持续竞争优势形成和企业成长。企业联盟成长包括联盟运行和联盟发展两个维度,企业联盟发展受联盟力的影响,而联盟企业、联盟力及其作用效果满足经典力学理论,据此构建企业联盟发展的力学模型,并通过对其公式推导,得到企业联盟发展的四大定理——"偏利共生"定理、"宇称不对称"定理、"大数中心"定理和"动态自稳定"定理及相关推论,而算例分析也对定理进行了验证,最后,相应提出了企业联盟发展的联盟网络、领先跟随、动态平衡与选择培育策略。     

A hybrid approach combining interior-point and branch-and-bound methods applied to the problem of sugar cane waste

This paper proposes a hybrid approach for solving the multi-objective model related to the minimisation of sugar cane waste collection costs and/or the maximisation of produced energy by this waste, with the aid of strategies for solving multi-objective problems, which transform the problem into a set of single-objective problems. This approach combines the predictor-corrector primal-dual interior-point and branch-and-bound methods in order to solve these single-objective problems. The model consists in identifying the sugar cane varieties with the lowest waste collection costs, while simultaneously it aims to obtain the greatest amount of produced energy by this waste. The hybrid methods are implemented in C++ programming language, and tests are performed to determine the efficient solutions in Pareto optimal sense of the multi-objective model and compare the performance of the hybrid method using the integrality test and without considering it. The mathematical results confirm that the proposed hybrid method for solving the aforementioned models presents good computational performance and reliable solutions.