Results 281 to 290 of about 576,260 (294)
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1997
Discrete mixture distribution models (MDM) assume that observed data do not stem from a homogeneous population of individuals but are a mixture of data from two or more latent populations (Everitt and Hand, 1981; Titterington et al., 1985). Applied to item response data this means that a particular IRT model does not hold for the entire sample but that
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Discrete mixture distribution models (MDM) assume that observed data do not stem from a homogeneous population of individuals but are a mixture of data from two or more latent populations (Everitt and Hand, 1981; Titterington et al., 1985). Applied to item response data this means that a particular IRT model does not hold for the entire sample but that
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1992
In demographic research, we often face situations where the dependent variable of interest is a dichotomy, such as dead or alive, divorced or still in marriage, accept or reject contraception, and so forth. In recent years, logistic regression has been used to study topics as diverse as marital formation and dissolution (Abdelrahman and Morgan, 1987 ...
K. Vaninadha Rao, Shiva S. Halli
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In demographic research, we often face situations where the dependent variable of interest is a dichotomy, such as dead or alive, divorced or still in marriage, accept or reject contraception, and so forth. In recent years, logistic regression has been used to study topics as diverse as marital formation and dissolution (Abdelrahman and Morgan, 1987 ...
K. Vaninadha Rao, Shiva S. Halli
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2019
Logistics is the lifeblood of any organization and especially so for organization in the Department of Defense. Logistics has been defined by individuals such as Jomini, as “the art of moving armies,” which includes providing for their supplies and establishing lines of supplies.
William P. Fox, Robert Burks
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Logistics is the lifeblood of any organization and especially so for organization in the Department of Defense. Logistics has been defined by individuals such as Jomini, as “the art of moving armies,” which includes providing for their supplies and establishing lines of supplies.
William P. Fox, Robert Burks
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The influence of variables in a logistic model
Biometrika, 1991SUMMARY The influence of explanatory variables in a logistic model is considered when the goal is to determine the predictive probability of a future observation in a Bayesian approach. We consider whether the predictive distribution will change greatly when subsets of the explanatory variables are omitted from the data set or from the future ...
S. K. Bhattacharjee, I. R. Dunsmore
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1998
The traditional theoretical focus of industrial location and linkage analysis is on the question of how transactions across space affect and influence market behaviour between points in space. Although such transactions take place in both space and time, time is rarely incorporated into space and location models, and where it is, this is usually done ...
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The traditional theoretical focus of industrial location and linkage analysis is on the question of how transactions across space affect and influence market behaviour between points in space. Although such transactions take place in both space and time, time is rarely incorporated into space and location models, and where it is, this is usually done ...
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2011
The chapter introduces logistic spline model that combines the principle of sigmoidal growth and the concept of interpolation splines. Logistic spline smoothly joins the latest (known) data about the number of product users with the assumed number of product users in future, and locally has a form of logistic law of growth .Applications of developed ...
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The chapter introduces logistic spline model that combines the principle of sigmoidal growth and the concept of interpolation splines. Logistic spline smoothly joins the latest (known) data about the number of product users with the assumed number of product users in future, and locally has a form of logistic law of growth .Applications of developed ...
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2011
Logistic model is widely used growth model with many useful properties for technological and market development forecasting. The chapter presents developed modifications of the model that are suitable for particular cases of new product adoption forecasting. Limitations of the logistic model are shown and discussed.
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Logistic model is widely used growth model with many useful properties for technological and market development forecasting. The chapter presents developed modifications of the model that are suitable for particular cases of new product adoption forecasting. Limitations of the logistic model are shown and discussed.
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1997
The vehicle routing models discussed in Part II assume that the frequency, timing and sizes of customer deliveries are predetermined. There are however many distribution problems in which the vehicle schedules and the timing and size of the customer deliveries are (or should be) simultaneously determined.
Julien Bramel, David Simchi-Levi
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The vehicle routing models discussed in Part II assume that the frequency, timing and sizes of customer deliveries are predetermined. There are however many distribution problems in which the vehicle schedules and the timing and size of the customer deliveries are (or should be) simultaneously determined.
Julien Bramel, David Simchi-Levi
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Modeling the Logistic Objectives
2011According to a well-known and perhaps already worn out saying from publications on management, one can only control what one can measure. This prerequisite holds true for the targeted control of logistic objectives, however, it alone is not enough.
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