Results 281 to 290 of about 58,720 (307)
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Dynamics of Epidemiological Models
Acta Biotheoretica, 2010We study the SIS and SIRI epidemic models discussing different approaches to compute the thresholds that determine the appearance of an epidemic disease. The stochastic SIS model is a well known mathematical model, studied in several contexts. Here, we present recursively derivations of the dynamic equations for all the moments and we derive the ...
Pinto, Alberto +3 more
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Journal of Political Economy, 1976
The usual neoclassical production function forms the point of departure for the present model of the firm. I will therefore briefly review the conceptual basis of capital and of the production function in the neoclassical model of the firm.' In the static model, maximization of profits under the competitive assumption yields the usual optimality ...
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The usual neoclassical production function forms the point of departure for the present model of the firm. I will therefore briefly review the conceptual basis of capital and of the production function in the neoclassical model of the firm.' In the static model, maximization of profits under the competitive assumption yields the usual optimality ...
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Multivariate Behavioral Research, 2017
Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series.
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Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series.
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IEEE Signal Processing Magazine, 2010
A graphical model consists of I a graph G = (V,E) and a V set of properties that determine a family of V probability distributions. There are many different types of graphs and properties, each determining a family. It is common to be able to develop algorithms that work for all members of the family by considering only a graph and its properties. Thus,
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A graphical model consists of I a graph G = (V,E) and a V set of properties that determine a family of V probability distributions. There are many different types of graphs and properties, each determining a family. It is common to be able to develop algorithms that work for all members of the family by considering only a graph and its properties. Thus,
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Proceedings of the 4th annual conference on Computer graphics and interactive techniques, 1977
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Characteristic Modeling Approach for High-Order Linear Dynamical Systems
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021Xinghuo Yu, Changyin Sun
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Data-driven reduced-order modeling for nonautonomous dynamical systems in multiscale media
Journal of Computational Physics, 2023Mengnan Li, Lijian Jiang
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How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems
Studies in Systems, Decision and Control, 2022Jan Treur
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