Inference in smoothing spline analysis of variance

Summary. Smoothing spline analysis of variance decomposes a multivariate function into additive components. This decomposition not only provides an efficient way to model a multivariate function but also leads to meaningful inference by testing whether a certain component equals 0. No formal procedure is yet available to test such a hypothesis. We propose an asymptotic method based on the likelihood ratio to test whether a functional component is 0. This test allows us to choose an optimal model and to compare groups of curves. We first develop the general theory by exploiting the connection between mixed effects models and smoothing splines. We then apply this to compare two groups of curves and to select an optimal model in a two-dimensional problem. A small simulation is used to assess the finite sample performance of the likelihood ratio test.     

航空公司交叉持股对产能共享策略的影响研究

产能共享与交叉持股是航空公司常用的运作与财务策略,两种方式都能在一定条件下起到缓和竞争的作用。本文考虑两家航空公司的两种交叉持股模式,构建了包含顾客忠诚度的价格竞争模型,依据产能是否对称以及是否实施产能共享策略形成八种不同的情形,求解并分析了不同情形下的最优价格决策及对应期望利润。通过对比不同情形下的利润,本文发现,在单向持股模式下,当产能对称时,两家企业始终愿意采用产能共享策略,而当产能不对称时,如果存在产能共享,产能较小的企业将更愿意降低产品价格,导致市场竞争加剧,从而损害产能较大企业的盈利能力。因此,只有当持股比例相对较小时企业才愿意实施共享产能策略。在交叉持股模式下,当产能对称时,企业在交叉持股比例适中时才愿意实施产能共享策略。而当产能不对称时,企业始终不愿意采用产能共享策略。这也表明产能共享和交叉持股策略之间存在一定的相互替代作用,企业应根据不同市场状态协调使用两种策略。     

Functional Mixed Effects Model for Small Area Estimation

Functional data analysis has become an important area of research because of its ability of handling high‐dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models and, in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area‐level data and fit a varying coefficient linear mixed effect model where the varying coefficients are semiparametrically modelled via B‐splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.     

An improved MIP heuristic for the intermodal hub location problem

Optimization methods have been commonly developed for the intermodal hub location problem because it has a broad range of practical applications. These methods include exact methods (limited on solving large-size problems) and heuristics (no guarantee on solution quality). In order to avoid their weakness but to leverage their strength, we develop an improved MIP heuristic combining branch-and-bound, Lagrangian relaxation, and linear programming relaxation. In the heuristic, we generate a population of initial feasible solutions using the branch-and-bound and Lagrangian relaxation methods and create a linear-relaxed solution using the linear programming relaxation method. We combine these feasible and linear-relaxed solutions to fix a portion of hub location variables so as to create a number of restricted hub location subproblems. We then combine the branch-and-bound method to solve these restricted subproblems for iteratively improving solution quality. We discuss in detail the application of the method to the intermodal hub location problem. The discussion is followed by extensive statistical analysis and computational tests, where the analysis shows statistical significance of solutions for guiding the heuristic search and comparisons with other methods indicate that the proposed approach is computationally tractable and is able to obtain competitive results.     

Rethinking integration in mixed methods research using data from different eras: lessons from a project about teenage vocational behaviour

Mixed methods research requires integration of qualitative and quantitative data. However, there is debate about how to define integration and what is required for integration to occur. This paper describes a mixed methods research project which revisits datasets from different eras, which were originally instigated for different purposes and had different theoretical frameworks. Using selected results about the relationship between teenagers’ vocational aspirations and adult occupations we show how the research topic and question integrated the projects within a constructivist theoretical position. We argue that reanalysing and comparing historical datasets can provide new insights into a topic even with minimal integration of the data. We recommend a broad definition of integration and reflexive research practice to encourage innovation and diversity in mixed methods research, particularly with regard to reanalysis of datasets from different eras.     

Learning from mixed OR method practice: The NINES case study

Despite continued interest in the use of mixed OR/MS methods, limited attention has been paid in the literature to generic lessons that could be gained from mixing methods in practice. Many organisational problems demand the use of a mixed method approach and thus recognising and sharing lessons could prove beneficial to both practitioners and researchers. This paper reports on an in-depth evaluation of a case study involving risk identification and quantification of the Northern Isles New Energy Solutions (NINES) project which sought to trial and plan a new energy system. The intervention involved a mixed method approach and client feedback on the efficacy of the approach was sought. The evaluation reported in this paper is carried out using a set of themes taken from the literature and seeks to highlight transferable lessons. The set of lessons that emerge are presented along with their implications for both general OR modelling practice and the specific situation of mixing OR/MS methods. The paper concludes by discussing the implications of the work and directions for future work which will be of interest to both practitioners and researchers interested in mixed method OR/MS work.     

Nature and role of customer satisfaction in the solution business

The paper focuses on the solution business. Here we argue that the strategy can only lead a company to perform better if it encompasses a direct and positive effect on satisfaction with a supplier’s consulting capabilities. Hence we introduce the concept of consulting satisfaction, identify antecedents and analyze its consequences. To do so, we apply a mixed-methods approach. Content analysis from open interviews with company professionals yields a list of antecedents of consulting satisfaction used to devise a set of hypotheses. The latter was translated into a questionnaire based measurement instrument in order to first collect and then analyze data from a larger sample survey. Since three of the antecedents could not be supported by our study, possible explanations are presented. With our approach we tap new dimensions of solutions research. First, we inaugurate research on buying behavior within the field of solutions. Second, we stress the role of capabilities in this field and extend service–profit chain thinking. And third, we present consulting satisfaction as a lever to translate the S-D logic of marketing into more practical applications. To our knowledge this is a novel insight and can help industry decision makers better prepare for the solution business.     

The analysis of mixed interval-censored and complete data

The article focuses mainly on a conditional imputation algorithm of quantile-filling to analyze a new kind of censored data, mixed interval-censored and complete data related to interval-censored sample. With the algorithm, the imputed failure times, which are the conditional quantiles, are obtained within the censoring intervals in which some exact failure times are. The algorithm is viable and feasible for the parameter estimation with general distributions, for instance, a case of Weibull distribution that has a moment estimation of closed form by log-transformation. Furthermore, interval-censored sample is a special case of the new censored sample, and the conditional imputation algorithm can also be used to deal with the failure data of interval censored. By comparing the interval-censored data and the new censored data, using the imputation algorithm, in the view of the bias of estimation, we find that the performance of new censored data is better than that of interval censored.     

On the Correlation of Common Factors with Variance Not Accounted for by the Factor Model

The case that the factor model does not account for all the covariances of the observed variables is considered. It is shown that principal components representing covariances not accounted for by the factor model can have a nonzero correlation with the common factors of the factor model. The substantial correlations of components representing variance not accounted for by the factor model with common factors are demonstrated in a simulation study comprising model error. Based on these results, a new version of Harman's factor score predictor minimizing the correlation with residual components is proposed.     

Probit and logistic discriminant functions

Most discriminant functions refer to qualitatively district groups. Talis et al. (1975) introduced the probit discriminant function for distinguishing between two ordered groups. They showed how to estimate this function for mixture sampling and continuous predictor variables. Here an estimation system is given for the more common separate sampling which is applicable to continuous and/or discrete predictor variables. When used solely with continuous variables) this method of estimation is more robust than Tallis!

The relationship of probit and logistic discrimination is discussed.