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A Polaris logistics model [PDF]
Naval Research Logistics Quarterly, 1964 AbstractThis paper presents a basic loss minimization model which has been applied in varying contexts for Polaris logistics problems. Definitive results are obtained in a general framework which extends the classic newsboy problem in two principal directions. First, probability distributions for demand are unrestricted. Second, a general framework for
Joseph P. Fennell +4 more
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PREDICTIVE DIAGNOSTICS FOR LOGISTIC MODELS
Statistics in Medicine, 1996Novel methodology is implemented to assess the predictive power of covariate information associated with sequential binary events. Logistic models are first fitted on the basis of a subset of the observations and then evaluated sequentially on the rest.
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International Journal of Physical Distribution & Materials Management, 1978
In a logistics system the number of possible applications of qualitative and quantitative modelling efforts is practically infinite. The situations or problems which can be analysed range from micro operations (e.g., analysing alternative order picking systems) to macro planning issues (e.g., determining the number and location of warehouses to be ...
Robert G. House, Jeffrey J. Karrenbauer
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In a logistics system the number of possible applications of qualitative and quantitative modelling efforts is practically infinite. The situations or problems which can be analysed range from micro operations (e.g., analysing alternative order picking systems) to macro planning issues (e.g., determining the number and location of warehouses to be ...
Robert G. House, Jeffrey J. Karrenbauer
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2019
Among the statistical preliminaries of education in the theory of gnostic clinical research, centrally important are, first, the precursors of logistic regression, culminating in the emergence of the General Linear Model; and then the generalization of this to the Generalized Linear Model, with logistic regression model a special case of this.
Albert Hofman +2 more
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Among the statistical preliminaries of education in the theory of gnostic clinical research, centrally important are, first, the precursors of logistic regression, culminating in the emergence of the General Linear Model; and then the generalization of this to the Generalized Linear Model, with logistic regression model a special case of this.
Albert Hofman +2 more
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A Generalized Logistic Tobit Model
Journal of quantitative economics, 1991This paper proposes the use of a generalisation of the Logistic distribution, the Burr Type II distribution, as the error structure in a Type I (Standard) Tobit model. The use of the Burr II is motivated through both an heterogeneity argument and by noticing the need for potentially non-symmetric distributions in Tobit models.
Fry, T, Orme, Chris D.
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1997
A supply chain is the collection of all components and functions associated with the creation and ultimate delivery of a product or service. Figure 2.1 illustrates an example product supply chain.
W. G. Nulty, H. D. Ratliff
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A supply chain is the collection of all components and functions associated with the creation and ultimate delivery of a product or service. Figure 2.1 illustrates an example product supply chain.
W. G. Nulty, H. D. Ratliff
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Biometrika, 2006
SUMMARY The multivariate logistic transform is a reparameterisation of cell probabilities in terms of marginal logistic contrasts. It is known that an arbitrary set of logistic contrasts may not correspond to a valid joint distribution. In this paper we present an efficient algorithm for detecting whether or not the inverse transform exists, and for ...
Bahjat F. Qaqish, Anastasia Ivanova
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SUMMARY The multivariate logistic transform is a reparameterisation of cell probabilities in terms of marginal logistic contrasts. It is known that an arbitrary set of logistic contrasts may not correspond to a valid joint distribution. In this paper we present an efficient algorithm for detecting whether or not the inverse transform exists, and for ...
Bahjat F. Qaqish, Anastasia Ivanova
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Logistic Regression Models [PDF]
, 2009 Preface Introduction The Normal Model Foundation of the Binomial Model Historical and Software Considerations Chapter Profiles Concepts Related to the Logistic Model 2 x 2 Table Logistic Model 2 x k Table Logistic Model Modeling a Quantitative Predictor Logistic Modeling Designs Estimation Methods Derivation of the IRLS Algorithm IRLS Estimation ...
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, 2003 Differential equation models, whether ordinary, delay, partial or stochastic, imply a continuous overlap of generations. Many species leave no overlap between successive generations and so population growth is in discrete steps. For primitive organisms, these discrete steps can be quite short, and hence a continuous (in time) model may be a reasonable ...
Anatoly Swishchuk, Jianhong Wu
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A program for logistic prediction modelling
Computer Programs in Biomedicine, 1985A computer program has been developed that can be used for analysing a binary outcome variable and a set of regressors of type interval with a logistic (i.e. nonlinear) model.
Björn Stenkvist +5 more
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