Results 211 to 220 of about 51,696 (258)

Linex discrepancy for bandwidth selection

Communications in Statistics - Simulation and Computation, 2017
ABSTRACTA bandwidth selection based on Linex discrepancy is proposed for kernel smoothing of periodogram. The selection minimizes Linex discrepancy between the smoothed and true spectrums. Two estimators are introduced for Linex discrepancy. The bandwidth choice outperforms some common bandwidth choices.
H. Mombeni, Sadegh Rezaei, Saralees Nadarajah   +2 more
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Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices

TEST, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chacón, J. E., Duong, T.
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On path selection for traffic with bandwidth guarantees

Proceedings 1997 International Conference on Network Protocols, 2002
Transmission of multimedia streams imposes a minimum-bandwidth requirement on the path being used to ensure end-to-end Quality-of-Service (QoS) guarantees. While any shortest-path algorithm can be used to select a feasible path, additional constraints that limit resource consumption and balance the network load are needed to achieve efficient resource ...
Qingming Ma, Peter Steenkiste
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Optimal bandwidth selection for MLS surfaces

2008 IEEE International Conference on Shape Modeling and Applications, 2008
We address the problem of bandwidth selection in MLS surfaces. While the problem has received relatively little attention in the literature, we show that appropriate selection plays a critical role in the quality of reconstructed surfaces. We formulate the MLS polynomial fitting step as a kernel regression problem for both noiseless and noisy data ...
Hao Wang, Carlos Eduardo Scheidegger, Cláudio T. Silva   +2 more
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Selection of bandwidth for kernel regression

Communications in Statistics - Theory and Methods, 2016
The most important factor in kernel regression is a choice of a bandwidth. Considerable attention has been paid to extension the idea of an iterative method known for a kernel density estimate to kernel regression. Data-driven selectors of the bandwidth for kernel regression are considered. The proposed method is based on an optimally balanced relation
Jan Koláček, Ivanka Horová
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Bandwidth selection in robust smoothing

Journal of Nonparametric Statistics, 1993
In robust smoothing of regression functions of the type , the theory in automatic bandwidth selection is still lacking. This paper tries to fill the gap by looking at the use of cross-validation methods in robust smoothing. Conjectures regarding the use of a class of robust cross-validation method are made.
Leung, Denis H. Y., Marriott, F. H. C., Wu, E. K. H.   +2 more
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Bandwidth selection in smoothing functions

East African Journal of Statistics, 2007
A simple criterion for selecting a bandwidth parameter that controls the amount of smoothing in functions is described. The procedure is computationally inexpensive and, hence, worth adopting. We argue that the bandwidth parameter is determined by two factors: the kernel function and the length of the smoothing region.
Kibua, T K, Karuku, M
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On Adaptive Bandwidth Selection for Efficient MIA

2014
Recently, a generic DPA attack using the mutual information index as the side channel distinguisher has been introduced. Mutual Information Analysis’s (MIA) main interest is its claimed genericity. However, it requires the estimation of various probability density functions (PDF), which is a task that involves the complicated problem of selecting ...
Carbone, Mathieu, Tiran, Sébastien, Ordas, Sébastien, Agoyan, Michel, Teglia, Yannick, Ducharme, Gilles R., Maurine, Philippe   +6 more
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Bandwidth Selection in Practice

1991
The choice of the bandwidth h is the main problem of kernel density estimation. In some situations it might be quite useful to have a set of estimates corresponding to different bandwidths. Those estimates can highlight different aspects in the structure of the data. However, the presentation and iterpretation of such curves is quite subjective.
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OPTIMAL BANDWIDTH SELECTION IN NONLINEAR COINTEGRATING REGRESSION

Econometric Theory, 2020
We study optimal bandwidth selection in nonparametric cointegrating regression where the regressor is a stochastic trend process driven by short or long memory innovations. Unlike stationary regression, the optimal bandwidth is found to be a random sequence which depends on the sojourn time of the process. All random sequences $h_{n}$ that lie within
Wang, Qiying, Phillips, Peter C. B.
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