cost function


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cost function

a mathematical formula created for the purpose of estimating a cost, e.g. the cost of making an observation when it varies from stratum to stratum of a collection of data.
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This approach relies on the penalization of the cost function adding prior information on the properties to be recovered.
The proposed FUEs cost function contains of linear pricing function and local gain term in which it has been applied inside the utility part of the cost function.
In this architecture, each interconnected subsystem has its own controller and individual cost function to optimize.
This article is structured as follows: section two introduces the standard model and studies the equivalence of the games induced by a convex and a concave transport cost function.
The first part is an estimation of coefficients for a translog cost function to determine which factors contribute to economies of scale and the extent to which they contribute for each of the five years in the period 2007 to 2011.
Economists use the multiple output cost function to analyze the behavior of a firm's costs.
where [lambda] is a weighting factor, which is another degree of freedom, g is the gradient of the cost function and H is the Hessian matrix.
Cost function approximation (CFA) covers policies where we minimize a cost function, usually modified in some way to achieve better long-term performance.
Cost function A is a nonlinear continuous arc-tangent approximation of a five-step piece-wise linear function, see Fig.
Note that, in the Capon beamforming algorithm [1], the cost function is p-dimensional, which is independent of the actual number of the incident signals N.
Nevertheless, there exist two main drawbacks in the formulation: (1) In the process of optimizing the cost function, Equation (3) punishes all iterative solutions in the same way regardless of desired or undesired one.
The cost function we estimate for local public health services embodies this balancing process, and for this reason, it is an ideal tool for estimating economies of scale and scope as it assumes LHJs are doing their best in choosing inputs to balance the benefits of using all inputs.