Comparison of strategies when building linear prediction models

In statistical and biometric sciences, one often uses predictive linear models. The initial form of such models is usually obtained by fitting the coefficients of the model to a set of observed data according to the classical least squares method. Newborn models that are obtained in this way will be referred to as raw models. Such raw models are often subject of efforts to improve them as to their predictive performance on external datasets. Several methods can be followed to fine‐tune raw models, thus leading to a variety of model building strategies. In this paper, the idea of so‐called victory rates is introduced to compare the performance of building strategies mutually.Copyright © 2013 John Wiley & Sons, Ltd.     

Solving the car sequencing problem via Branch & Bound

In a mixed-model assembly line, varying models of the same basic product are to be produced in a facultative sequence. This results to a short-term planning problem where a sequence of models is sought which minimizes station overloads. In practice – e.g. the final assembly of cars – special sequencing rules are enforced which restrict the number of models possessing a certain optional feature k to r_k within a subsequence of s_k successive models. This problem is known as car sequencing. So far, employed solution techniques stem mainly from the field of Logic and Constraint Logic Programming. In this work, a special Branch & Bound algorithm is developed, which exploits the problem structure in order to reduce combinatorial complexity.     

A Galois correspondence for countable short recursively saturated models of PA

In this paper we investigate the properties of automorphism groups of countable short recursively saturated models of arithmetic. In particular, we show that Kaye's Theorem concerning the closed normal subgroups of automorphism groups of countable recursively saturated models of arithmetic applies to automorphism groups of countable short recursively saturated models as well. That is, the closed normal subgroups of the automorphism group of a countable short recursively saturated model of PA are exactly the stabilizers of the invariant cuts of the model which are closed under exponentiation. This Galois correspondence is used to show that there are countable short recursively saturated models of arithmetic whose automorphism groups are not isomorphic as topological groups. Moreover, we show that the automorphism groups of countable short arithmetically saturated models of PA are not topologically isomorphic to the automorphism groups of countable short recursively saturated models of PA which are not short arithmetically saturated (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A two-stage parallel branch and bound algorithm for mixed integer programs

Mixed integer programming (MIP) models are extensively usedto aid strategic and tactical decision making in many businesssectors. Solving MIP models is a computationally intensive processand there is a need to develop solution approaches that enablelarger models to be solved within acceptable timeframes. Inthis paper, we describe the implementation of a two-stage parallelbranch and bound (PB & B) algorithm for MIP. In stage 1of the algorithm, a multiple heuristic search is implementedin which a number of alternative search trees are investigatedusing a forest search in the hope of finding a good solutionquickly. In stage 2, the search is reorganized so that the branchesof a chosen tree are investigated in parallel. A new heuristicis introduced, based on a best projection criterion, which evaluatesalternative B & B trees in order to choose one for investigationin stage 2 of the algorithm. The heuristic also serves as away of implementing a quality load balancing scheme for stage2 of the algorithm. The results of experimental investigationsare reported for a range of models taken from the MIPLIB libraryof benchmark problems.     

Harvesting discrete nonlinear age and stage structured populations

A natural extension of age structured Leslie matrix models is to replace age classes with stage classes and to assume that, in each time period, the transition from one stage class to the next is incomplete; that is, diagonal terms appear in the transition matrix. This approach is particularly useful in resource systems where size is more easily measured than age. In this linear setting, the properties of the models are known; and these models have been applied to the analysis of population problems. A more applicable setting is to assume that the reproduction, survival, and transition parameters in the model are density dependent. The behavior of such models is determined by the form of this density dependence. Here, we focus on models in which the parameters depend on the value of an aggregated variable, defined to be the weighted sum of the number of individuals in each stage class. In forestry models, for example, this aggregated variable may represent a basal area index; in fisheries models, it may represent a spawning stock biomass. Current age structured nonlinear stock-recruitment fisheries models are a special case of the models considered here. Certain results that apply to age structured models can be extended to this broader class of models. In particular, the questions addressed relate to the minimum number of age classes that need to be harvested to obtain maximum sustainable yield policies and to managing resources under nonequilibrium and stochastic conditions. Application of the model to problems in fisheries, forestry, pest, and wildlife management is also discussed.The author would like to thank R. G. Haight for comments and discussions relating to the material presented here. This work was supported by NSF Grant DMS-85-11717.     

The Robustness of Multi-echelon Service Models under Autocorrelated Demands

A common assumption underlying the development of multi-echelon service models is that successive demands are independent. In this paper we study the robustness of two models, developed for a two-echelon serial inventory network, when the demand process is autocorrelated. Both stockpoints operate a periodic review order-up-to-S echelon inventory policy. Using an analytic approach, we extend the original models so that they apply exactly for any autocorrelated period demand process and explore the behaviour of the extended models under different scenarios. In order to study the effects of different autocorrelation characteristics, an MA(1) and an AR(1) process are analysed in detail. Our results demonstrate that, depending on the overall system parameters setting, models which ignore the effects of autocorrelation may provide very unsatisfactory estimates of the system performance. Hence, extreme caution is required when deciding the use of multi-echelon service models in practice.     

A class of subgrid-scale models preserving the symmetry group of Navier–Stokes equations

Navier–Stokes equations (NS) admit transformations which transform a solution to another solution (galilean transformation, scaling transformation, …). They also admit viscosity dependent transformations which transform a solution to a solution of another NS with different viscosity. These particular transformations are called symmetries of NS. Each of them has a physical role (such as conservation laws, …). A consistent turbulence model should then remain invariant under these symmetry transformations. Unfortunately, this is not the case of several models.In this article, a class of subgrid-scale models preserving the symmetries of NS is built. This class is then refined such that the models respect the second law of thermodynamics. One of the simplest models of the class is tested to the flow in a ventilated room. Better results than those provided by Smagorinsky and dynamic models are obtained.     

A chance-constrained approach to stochastic line balancing problem

In this paper, chance-constrained 0–1 integer programming models for the stochastic traditional and U-type line balancing (ULB) problem are developed. These models are solved for several test problems that are well known in the literature and the computational results are given. In addition, a goal programming approach is presented in order to increase the system reliability, which is arising from the stochastic case.     

Topological flatness of local models for ramified unitary groups. I. The odd dimensional case

Local models are certain schemes, defined in terms of linear-algebraic moduli problems, which give étale-local neighborhoods of integral models of certain p-adic PEL Shimura varieties defined by Rapoport and Zink. When the group defining the Shimura variety ramifies at p, the local models (and hence the Shimura models) as originally defined can fail to be flat, and it becomes desirable to modify their definition so as to obtain a flat scheme. In the case of unitary similitude groups whose localizations at Qp are ramified, quasi-split GUn, Pappas and Rapoport have added new conditions, the so-called wedge and spin conditions, to the moduli problem defining the original local models and conjectured that their new local models are flat. We prove a preliminary form of their conjecture, namely that their new models are topologically flat, in the case n is odd.     

On generalized shock models for deteriorating systems

Standard assumptions in shock models are that failures of items are related either to the cumulative effect of shocks (cumulative models) or that they are caused by shocks that exceed a certain critical level (extreme shocks models). In this paper, we present useful generalizations of this setting to the case when an item is deteriorating itself, for example, when the boundary for the fatal shock magnitude is decreasing with time. Three stochastic failure models describing different impacts of shocks on items are considered. The cumulative effect of shocks is modeled in a way similar to the proportional hazards model. Explicit formulas for the corresponding survival functions are derived and several simple examples are considered. Copyright © 2012 John Wiley & Sons, Ltd.     

Empirical validation of a queueing approach to uninterrupted traffic flows

In this paper, the use of queueing theory for modeling uninterrupted traffic flows is evaluated. Empirical data on speeds and flows are used to evaluate speeds generated by the different queueing models. Using the Theil inequality coefficient as evaluation criterion, the speeds generated by the queueing models are compared to the empirical speeds. Queueing models that best fit the observed speeds are obtained. It appears that traffic flow on a highway during non-congested hours is best described using a M/G/1 queueing model. During the congested hours however, the state dependent queueing GI/G/z models are more realistic. Because the queueing models describe the empirical data well, they can also be used to evaluate potential improvements in existing traffic conditions. Received: April 2005 / Revised version: June 2005 AMS classification: 60K30, 68M20     

The concept ‘model’ and its potential role in mathematics education

Under the general term ‘mathematical models’ is now subsumed a sufficiently diversified collection of distinct types of models to merit categorization and an attempt at a unified definition. In this study a broad ‘working definition’ for the concept ‘model’ is proposed; basic types of models are identified and illustrated, and the impact of conscious instruction of models on mathematics education is analysed.     

A ranking method based on a full-inefficient frontier

Since in evaluating by traditional data envelopment analysis (DEA) models many decision making units (DMUs) are classified as efficient, a large number of methods for fully ranking both efficient and inefficient DMUs have been proposed. In this paper a ranking method is suggested which basically differs from previous methods but its models are similar to traditional DEA models such as BCC, additive model, etc. In this ranking method, DMUs are compared against an full-inefficient frontier, which will be defined in this paper. Based on this point of view many models can be designed, and we mention a radial and a slacks-based one out of them. This method can be used to rank all DMUs to get analytic information about the system, and also to rank only efficient DMUs to discriminate between them.     

New MILP models for the permutation flowshop problem

Two new mixed-integer linear programming (MILP) models for the regular permutation flowshop problem, called TBA and TS3, are derived using a combination of JAML (job-adjacency, machine-linkage) diagrams and variable substitution techniques. These new models are then compared to the incumbent best MILP models (Wilson, WST2, and TS2) for this problem found in the flowshop sequencing literature. We define the term best to mean that a particular model or set of models can solve a common set of test flowshop problems in significantly less time than other competing models. In other words, the two new MILP models (TBA and TS3) become the challengers to the current incumbent best models (Wilson, WST2, TS2.). Both new models are shown to require less time, on average, than the current best models for solving this set of problems; and the TS3 model is shown to solve these problems in statistically significantly less time than the other four models combined.     

Variational Solutions of the Pricing PIDEs for European Options in Lévy Models

Abstract

One of the fundamental problems in financial mathematics is to develop efficient algorithms for pricing options in advanced models such as those driven by Lévy processes. Essentially there are three approaches in use. These are Monte Carlo, Fourier transform and partial integro-differential equation (PIDE)-based methods. We focus our attention here on the latter. There is a large arsenal of numerical methods for efficiently solving parabolic equations that arise in this context. Especially Galerkin and Galerkin-inspired methods have an impressive potential. In order to apply these methods, what is required is a formulation of the equation in the weak sense.

The contribution of this paper is therefore to analyse weak solutions of the Kolmogorov backward equations which are related to prices of European options in (time-inhomogeneous) Lévy models and to establish a precise link between the prices and the weak solutions of these equations. The resulting relation is a Feynman–Kac representation of the solution as a conditional expectation. Our special concern is to provide a framework that is able to cover both, the common types of European options and a wide range of advanced models in which these derivatives are priced.

An application to financial models requires in particular to admit pure jump processes such as generalized hyperbolic processes as well as unbounded domains of the equation. In order to deal at the same time with the typical pay-offs that can arise, the weak formulation of the equation is based on exponentially weighted Sobolev–Slobodeckii spaces. We provide a number of examples of models that are covered by this general framework. Examples of options for which such an analysis is required are calls, puts, digital and power options as well as basket options.     

On statistical models for regression diagnostics

In regression diagnostics, the case deletion model (CDM) and the mean shift outlier model (MSOM) are commonly used in practice. In this paper we show that the estimates of CDM and MSOM are equal in a wide class of statistical models, which include LSE, MLE, Bayesian estimate andM-estimate in linear and nonlinear regression models; MLE in generalized linear models and exponential family nonlinear models; MLEs of transformation parameters of explanatory variables in a Box-Cox regression models and so on. Furthermore, we study some models, in which, the estimates are not exactly equal but are approximately equal for CDM and MSOM.     

A general framework for distance-based consensus in ordinal ranking models

The problem of aggregating a set of ordinal rankings of n alternatives has given rise to a number of consensus models. Among the most common of these models are those due to Borda and Kendall, which amount to using average ranks, and the ℓ¹ and ℓ² distance models. A common criticism of these approaches is their use of ordinal rank position numbers directly as the values of being ranked at those levels. This paper presents a general framework for associating value or worth with ordinal ranks, and develops models for deriving a consensus based on this framework. It is shown that the ℓ^p distance models using this framework are equivalent to the conventional ordinal models for any p ⩾ 1. This observation can be seen as a form of validation of the practice of using ordinal data in a manner for which it was presumably not designed. In particular, it establishes the robustness of the simple Borda, Kendall and median ranking models.     

Challenge Versus Exchange in Collective Decision Making: A Comparison of Two Simulation Models Based on Simulated Data

In collective decision making, actors can use different influence strategies to get their way. Differences in influence strategies may, or may not, be connected to differences in collective outcomes. This research studies two influence strategies: the exchange strategy and the challenge strategy. In the existing literature, these strategies are analyzed and compared using simulation models in which actor behavior regarding influence attempts based on one of the strategies is modeled explicitly. Until now, these models have been tested only empirically on limited data sets. However, a theoretical test is necessary to gain more precise insights in the effect of characteristics of collective decision making situations on the collective outcomes. In the present research, computer simulations are used in a structured comparison of two competing models (the iterative exchange model and challenge model). The analyses show that the outcomes of both models are captured for a large part in the actor characteristics on the issues. Besides this, the expected directions of challenges and exchanges play a major part in explaining the outcomes of the models. This research shows that the use of simulated data allows a structured search of the input space, which led to new insights into the iterative exchange model and challenge model, and therefore in the exchange strategy and the challenge strategy.     

Local models of Shimura varieties and a conjecture of Kottwitz

We give a group theoretic definition of “local models” as sought after in the theory of Shimura varieties. These are projective schemes over the integers of a p-adic local field that are expected to model the singularities of integral models of Shimura varieties with parahoric level structure. Our local models are certain mixed characteristic degenerations of Grassmannian varieties; they are obtained by extending constructions of Beilinson, Drinfeld, Gaitsgory and the second-named author to mixed characteristics and to the case of general (tamely ramified) reductive groups. We study the singularities of local models and hence also of the corresponding integral models of Shimura varieties. In particular, we study the monodromy (inertia) action and show a commutativity property for the sheaves of nearby cycles. As a result, we prove a conjecture of Kottwitz which asserts that the semi-simple trace of Frobenius on the nearby cycles gives a function which is central in the parahoric Hecke algebra.     

The Theory of Finite Models without Equal Sign

In this paper, it is the first time ever to suggest that we study the model theory of all finite structures and to put the equal sign in the same situtation as the other relations. Using formulas of infinite lengths we obtain new theorems for the preservation of model extensions, submodels, model homomorphisms and inverse homomorphisms. These kinds of theorems were discussed in Chang and Keisler＇s Model Theory, systematically for general models, but Gurevich obtained some different theorems in this direction for finite models. In our paper the old theorems manage to survive in the finite model theory. There are some differences between into homomorphisms and onto homomorphisms in preservation theorems too. We also study reduced models and minimum models. The characterization sentence of a model is given, which derives a general result for any theory T to be equivalent to a set of existential-universal sentences. Some results about completeness and model completeness are also given.