Generalising the Parametric Selection Functions Approach
Environmental Efficiency Measurement with Translog Distance Functions: A Parametric Approach
... of parametric distance functions intended to be applied in environmental efficiency and productivity ...their parametric specification of a translog hyperbolic distance function to mirror the ...
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Monte Carlo Simulation for Modified Parametric Of Sample Selection Models Through Fuzzy Approach
... It appears very suitable for modeling vague concepts. It is diffi- cult to determine some of the criteria and arrive at a quantitative value. Fuzzy sets theory and its properties through the concept of fuzzy number. The ...
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A Semi-Parametric Approach to the Oaxaca–Blinder Decomposition with Continuous Group Variable and Self-Selection
... Fernando Rios-Avila Levy Economics Institute, Bard College, Annandale-on-Hudson, NY 12504, USA; [email protected] Received: 22 February 2019; Accepted: 18 June 2019; Published: 21 June 2019 Abstract: This paper presents ...
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Parametric estimation of risk neutral density functions
... on parametric estimation methods for the risk neutral density functions determining the risk neutral distribu- ...indirect approach is to calibrate characteristic parameter vectors for stochastic ...
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The parametric characteristics of frequency response functions for nonlinear systems
... the parametric characteristics of the frequency response functions for nonlinear systems are ...The parametric characteristics of the GFRFs and the system output spectrum can easily be achieved using ...
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A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions.
... Apart from various rules of thumb Baddeley et al., 2015, § 6.5; Illian et al., 2008, § 3.3; Scott, 1992, § 6; or the first edition of Diggle, 2014, there are essentially two main approach[r] ...
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Energy based approach for shape parameter selection in radial basis functions collocation method
... parameter selection in radial basis function is ...consistent approach for estimating the optimal shape parameter, i.e., an approach based on the Princi- ple of Minimum of Total Potential ...proposed ...
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Fitting Weibull ACD Models to High Frequency Transactions Data: A Semi-parametric Approach based on Estimating Functions
... semi- parametric approach based on the theory of estimating functions ...EF approach is easier to apply in practice and gives better estimates than the ...EF approach is compatible with ...
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A Non Parametric Approach to Spatial Causality
... Section 5.1 focuses on the application of Theorem 4.1; that is, on the measure of the conditional entropy of (19) as a criterion for selecting the most important weighting matrix in a causal relation. The concern of ...
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A Non-Parametric Approach to Dynamic Programming
... Value functions are an essential concept for determining optimal policies in both optimal con- trol [1] and reinforcement learning [2, ...value functions and determining better policies is known as policy ...
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PARAMETRIC GEOMETRIC PROGRAMMING (FPGP) APPROACH
... by parametric Geometric-Programming ...membership functions such as piecewise linear hyperbolic, L-R fuzzy number, Trapezoidal Fuzzy Number (TrFN), Parabolic flat Fuzzy Number (PfFN), Parabolic Fuzzy Number ...
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Parametric Portfolio Selection: Evaluating and Comparing to Markowitz Portfolios
... the parametric portfolio optimization out of sample performance and it yielded higher returns than the market and the out of sample Markowitz based, even when transaction costs are ...the parametric ...
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Selection functions in doppler planet searches
... The other method presented by Marcy et al. (2005) is empirical and involves creating 1000 or more quasi-artificial data sets by generating randomly scrambling the velocities, but keeping the times the same, and then ...
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A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer
... In principle our method allows consideration of a large number of components of exposure. In our particular case, we have also explored the respective role of dark versus light tobacco and filtered versus non filtered ...
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R&D and Subsidies at the Firm Level: An Application of Parametric and Semi-Parametric Two-Step Selection Models
... Robinson (And./Schafg.) 0.12*** *** significance at the 1% level All estimated models provide a positive impact of public R&D granting on firms’ R&D expenditure. The magnitude of this effect varies with the applied model ...
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R&D and Subsidies at the Firm Level: An Application of Parametric and Semi-Parametric Two-Step Selection Models
... Robinson (And./Schafg.) 0.12*** *** significance at the 1% level All estimated models provide a positive impact of public R&D granting on firms’ R&D expenditure. The magnitude of this effect varies with the applied model ...
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A Parametric Bayesian Approach in Density Ratio Estimation
... a parametric Bayesian approach, when distributions come from the canonical form of the exponential ...loss functions with the possibility of being exactly equal when the correction factor H = ...
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A Case Study on Meta-Generalising: A Gaussian Processes Approach
... Five different data sets are considered in the experiments. The first two data sets are artificially generated to demonstrate the strengths and the limitations of the method; the first one satisfies the assumptions of ...
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Parametric, Vector, and Polar Functions
... We can then identify each point P in the plane by polar coordinates ( r , ), where r gives the directed distance from O to P and gives the directed angle from the initial ray to th[r] ...
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Generalising Conflict Networks
... Therefore, the interplay of battlefield values, the initial endowment and properties of the the impact function f(.) determine whether the game has a unique Nash equilibrium. Note that the case a i = a j = 1 and v ij = v ...
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