Eigenvalue Decay and Smooth Regression Functions
Decay functions in commodity freight flow models A regression model for deriving the decay parameter
... high decay parameter that would justify a different treatment from the other commodity groupings at this ...between decay and possible influencing ...the decay parameters to the commodity groupings ...
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Accelerating the DC algorithm for smooth functions
... posite functions have been extensively investigated and found applications to many problems such as: inverse covariance estimate, logistic regression, sparse least squares and feasibility problems, see ...
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Representing Functional Data as Smooth Functions
... as smooth functions, and smoothing techniques for estimation out of discretely observed ...penalized regression and how to compute penalty ...
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Smooth ε-Insensitive Regression by Loss Symmetrization
... In this section we present experimental results that demonstrate different aspects of our algorithms in the light of their formal analysis. In Section 8.1, we start with a synthetic example that underscores the different ...
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Experiments on polynomial (chaos) approximation of maximum eigenvalue functions: Tutorial
... of smooth, non-differentiable and not even Lipschitz continuous benchmark functions in the univariate and bivariate ...analyzed functions arise from parameter eigenvalue prob- lems; more in ...
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Smooth Transition Regression Models in UK Stock Returns
... Graphs 2-3 display the transition functions. The estimated slope parameter values for each model imply very different dynamics around the threshold parameters. According to the first model, the large value of the ...
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Regression density estimation using smooth adaptive Gaussian mixtures
... Similarly, let W (r×m) and Z (q×m) denote the variable selection indicators for the variance and mixing functions, respectively. We would like to emphasize that many problems encountered in economics will not re- ...
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Strictly monotone and smooth nonparametric regression for two or more variables
... nonparametric regression with an one- dimensional predictor applies isotonic regression, which is easily implemented for functions of one variable using the pool-adjacent violator algorithm ...for ...
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Regularised forecasting via smooth-rough partitioning of the regression coefficients
... basis functions for the normalised B-splines {B h } ...basis functions to approximate the infinite-dimensional ...is smooth, which is the case we are interested ...
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Strictly monotone and smooth nonparametric regression for two or more variables
... nonparametric regression with an one- dimensional predictor applies isotonic regression, which is easily implemented for functions of one variable using the pool-adjacent violator algorithm ...for ...
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Adaptive Confidence Bands for Nonparametric Regression Functions
... The proposed confidence band procedure can be implemented efficiently in standard sta- tistical software with wavelet support. Numerical performance of the procedure is investi- gated using both simulated examples and a ...
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Smooth eigenvalue correction
... population eigenvalue estimates, showing sig- nificant differences between estimates, and none of the estimates matches closely with the real population eigen- ...population eigenvalue estimates and show ...
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Smooth functions statistics
... The total number of the choices is (2T − 1)(2T + 1) < 4T 2 , proving the Lemma. These reasonings prove in fact more, than stated: one evaluates this way the larger number, including those ordered graphs, for which the ...
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Smooth backfitting in additive inverse regression
... additive regression model ...2 smooth backfitting [see Mammen et ...inverse regression models [see Diggle and Hall (1993) or Mair and Ruymgaart ...the smooth backfitting approach observed in ...
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Panel Smooth Transition Regression Models
... Keywords: financial constraints; heterogenous panel; investment; misspecification test; nonlinear modelling panel data; smooth transition models. JEL Classification Codes: C12, C23, C52, G31, G32. ∗ This research ...
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On the Interpolation of Smooth Functions via Radial Basis Functions
... limited functions via translates of ...bandlimited functions whose band lies in a ball of small radius β, where the interpolation is done at a Riesz-basis sequence for some larger symmetric convex body (per ...
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A generalized eigenvalue problem for quasi-orthogonal rational functions
... Definition 4. We call a rational function Q n ∈ L n \ L n−1 , n > 0, a qORF iff Q n ⊥ F L n−1 (α n ). In theorem 5 below we will show that the zeros of this Q n indeed will depend on one parameter τ n ∈ C. As we will see ...
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Sigmoid functions for the smooth approximation to x
... x 2 + µ with respect to accuracy. To accom- plish our goal we also provide sharp hyperbolic bounds for error function. 1 Introduction An S - shaped function which usually monotonically increases on R (the set of all real ...
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Spectral Bandits for Smooth Graph Functions
... INRIA Lille - Nord Europe, SequeL team, 40 avenue Halley 59650, Villeneuve d’Ascq, France Abstract Smooth functions on graphs have wide applica- tions in manifold and semi-supervised learning. In this ...
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Smooth muscle cells are important for the functions
... The expression of SM22a in smooth, cardiac, and skeletal muscle cells raises the possibility that these different muscle cell types may share a common myo- genic regulatory program early[r] ...
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