Setting the Regularization Parameter using the Evidence
Microeconomic Evidence on Price-Setting
... Shocks Evidence on the response of prices to identified shocks is particularly useful for shedding light on the nature of firms’ price-setting decisions because most (if not all) theories of ...
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Understanding and using patient experiences as evidence in healthcare priority setting
... patient evidence is necessary to sup- port a fair process of decision-making has broad impli- cations for all decisions made that affect patients’ access to ...patient evidence should be added to these ...
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Efficiency for Regularization Parameter Selection in. Penalized Likelihood Estimation of Misspecified Models
... example setting a = ...tuning parameter of SCAD is fixed at ...recommend using a data-dependent choice of a since it requires little additional cost and can greatly improve the performance of all of ...
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Automatic parameter setting for Arnoldi-Tikhonov methods
... In this paper we have proposed an approximated version of the classical dis- crepancy principle that can be easily coupled with the iterative scheme of the Arnoldi-Tikhonov method, since it simultaneously determines the ...
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Categorical Acquisition: Parameter-Setting in Universal Grammar
... each parameter). Each value of a parameter begins with a roughly 50–50 chance of “success” at the ...the parameter that fails to parse the input is punished and devalued, thereby indirectly favoring ...
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Automatic parameter setting for Arnoldi-Tikhonov methods
... In this paper we have proposed an approximated version of the classical dis- crepancy principle that can be easily coupled with the iterative scheme of the Arnoldi-Tikhonov method, since it simultaneously determines the ...
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Efficiency and Consistency for Regularization Parameter Selection in Penalized Regression: Asymptotics and Finite-Sample Corrections
... Furthermore, the results appear to be consistent with Wang et al. (2009) who found that sample sizes that are around 1600 are required before the percentage of times that the true model is selected is close to 100%. ...
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Proposition of patient stratification and parameter setting for mechanical traction in patients with LBP
... of evidence supporting its effectiveness in the work of inspection in recent years is the poor quality of research, postulated by the authors of these works ...
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Using Benson’s Algorithm for Regularization Parameter Tracking
... one regularization term, ...single regularization parameter α, is traditionally called the regularization ...linear regularization paths has been developed and exact path following ...
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Regularization of a Parameter Estimation Problem using Monotonicity and Convexity Constraints *
... Abstract. In marine science, it is usually assumed that there is a functional relationship between the parental population size and subsequent offsprings. The function is referred to as the Stock Recruitment Function ...
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An Iterative Method for the Solution of Nonlinear Regularization Problems with Regularization Parameter Estimation
... the regularization parameter λ is computed by means of the Generalized Cross Validation function gcv [15], while the function lsqi computes the regularization parameter by solving the ...
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On Statistical Parameter Setting
... words. Using this set of words it is possible to cluster the lexical inventory into open and closed class words, as well as to identify the subclasses of nouns and verbs in the open ...
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A parameter-adaptive iterative regularization model for image denoising
... scale parameter is proposed in order to decrease the sensitivity of constant scale par- ameter, optimize the scale parameter adaptively in the IRM, and attain a desirable level of applicability for image ...
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An Effective Scheme for Estimating a Smoother Parameter in the Method of Regularization
... the regularization method and the evaluation by generalized CV with an influence function ...smoother parameter which can minimize the value of the evaluation ...model using information criteria such ...
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Dual-parameter regularization method in three-dimensional ionospheric reconstruction
... density using the dual-parameter regularization method show further improvement compared with that using the single-parameter regularization ...
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Two-parameter regularization method for an axisymmetric inverse heat problem
... problem. Using the modified quasi-boundary value (MQBV) method with two regularization parameters, one related to the error in measurement process and the other related to the regularity of solution, ...
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Regularization parameter selection in indirect regression by residual based bootstrap
... estimator using either a cross–validation or bootstrap approach, which can then be min- imized with respect to the choice of bandwidth in an exact or approximate ...estimator using a smooth bootstrap of ...
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Regularization in fractional order Sobolev spaces for a parameter identification problem
... We assume furthermore that the mesh size converges to zero as the number of elements of the triangulation tends to infinity. In the literature a uniform triangulation T h is also called regular or isotropic. By a finite ...
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Urban Transit Frequency Setting using Multiple Tabu Search with Parameter Control
... frequency setting is one of the multiobjective problems in public transportation system, which aims to find optimal time interval between subsequent buses along the ...chosen parameter gives considerable ...
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Meta-raps: Parameter Setting And New Applications
... by using a heuristic that uses techniques from response surface methodology and the ...defined parameter settings experimental design then plotting the regression equation and moving away from the design ...
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