Adaptive Kernel Estimation of a Cusp-shaped Mode

1996 ◽  
pp. 109-120 ◽  
Author(s):  
W. Ehm
Keyword(s):  
Kernel Estimation ◽  
Adaptive Kernel

Adaptive kernel estimation of spatial relative risk

2010 ◽  
Vol 29 (23) ◽  
pp. 2423-2437 ◽  
Author(s):  
Tilman M. Davies ◽  
Martin L. Hazelton
Keyword(s):  
Relative Risk ◽  
Kernel Estimation ◽  
Adaptive Kernel

scholarly journals Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates

2016 ◽  
Vol 148 ◽  
pp. 141-159 ◽  
Author(s):  
Agathe Guilloux ◽  
Sarah Lemler ◽  
Marie-Luce Taupin
Keyword(s):  
Cox Model ◽  
Kernel Estimation ◽  
High Dimensional ◽  
Adaptive Kernel

scholarly journals A Consistent Geological-Seismological Model For Earthquake Occurrence in New Zealand

2021 ◽  
Author(s):  
◽  
Christian Stock
Keyword(s):  
New Zealand ◽  
Active Faults ◽  
Kernel Estimation ◽  
Fault Model ◽  
Strike Slip ◽  
Historical Earthquake ◽  
Earthquake Occurrence ◽  
Model Based ◽  
Adaptive Kernel ◽  
Dynamic Stochastic

<p>For the development of earthquake occurrence models, historical earthquake catalogues and compilations of mapped, active faults are often used. The goal of this study is to develop new methodologies for the generation of an earthquake occurrence model for New Zealand that is consistent with both data sets. For the construction of a seismological earthquake occurrence model based on the historical earthquake record, 'adaptive kernel estimation' has been used in this study. Based on this method a technique has been introduced to filter temporal sequences (e.g. aftershocks). Finally, a test has been developed for comparing different earthquake occurrence models. It has been found that the adaptive kernel estimation with temporal sequence filtering gives the best joint fit between the earthquake catalogue and the earthquake occurrence model, and between two earthquake occurrence models obtained from data from two independent time intervals. For the development of a geological earthquake occurrence model based on fault information, earthquake source relationships (i.e. rupture length versus rupture width scaling) have been revised. It has been found that large dip-slip and strike-slip earthquakes scale differently. Using these source relationships a dynamic stochastic fault model has been introduced. Whereas earthquake hazard studies often do not allow individual fault segments to produce compound ruptures, this model allows the linking of fault segments by chance. The moment release of simulated fault ruptures has been compared with the theoretical deformation along the plate boundary. When comparing the seismological and the geological earthquake occurrence model, it has been found that a 'good' occurrence model for large dip-slip earthquakes is given by the seismological occurrence model using the Gutenberg-Richter magnitude frequency distribution. In contrast, regions dominated by long strike-slip faults produce large earthquakes but not many small earthquakes and the occurrence of earthquakes on such faults should be inferred from the dynamic fault model.</p>

Blur Kernel Optimization: A New Approach to Patch Selection with Adaptive Kernel Estimation

2013 ◽  
Vol 436 ◽  
pp. 531-538 ◽  
Author(s):  
Saqib Yousaf ◽  
Shi Yin Qin
Keyword(s):  
Computational Cost ◽  
Kernel Estimation ◽  
Local Binary Patterns ◽  
Image Deconvolution ◽  
Patch Selection ◽  
Image Patches ◽  
Adaptive Kernel ◽  
Speed Up ◽  
Kernel Optimization ◽  
Selection Of

Recently, many effective approaches appeared in the field of blind image deconvolution to reduce the computational cost. Using multiple smaller regions instead of whole image not only make the restoration efficient but also improves the results by discarding the ineffectual regions. It is observed that a study is needed to compare different methods for the selection of useful image patches and different schemes to utilize their blur kernels, which is aimed in the present work. A new patch selection method using Contrast based blur invariant features (CBIF) is proposed to find the useful regions which gives better results compared with others e.g., speed-up robust features (SURF), local binary patterns (LBP), local phase quantization (LPQ), maximally stable extremal regions (MSER), Canny and Sobel. In addition, gradually increasing contrast stretched levels shown to give better results compared with commonly used multiscale framework to avoid false local minima. It is also proposed that blur metric by Crete applied on latent image can be used for the selection of better kernel. It is observed that an effective strategy can give good results even when the patches are not selected carefully. The best results are obtained when our proposed patch selection is used with our “selective kernels averaging” scheme.

scholarly journals A Consistent Geological-Seismological Model For Earthquake Occurrence in New Zealand

2021 ◽  
Author(s):  
◽  
Christian Stock
Keyword(s):  
New Zealand ◽  
Active Faults ◽  
Kernel Estimation ◽  
Fault Model ◽  
Strike Slip ◽  
Historical Earthquake ◽  
Earthquake Occurrence ◽  
Model Based ◽  
Adaptive Kernel ◽  
Dynamic Stochastic

<p>For the development of earthquake occurrence models, historical earthquake catalogues and compilations of mapped, active faults are often used. The goal of this study is to develop new methodologies for the generation of an earthquake occurrence model for New Zealand that is consistent with both data sets. For the construction of a seismological earthquake occurrence model based on the historical earthquake record, 'adaptive kernel estimation' has been used in this study. Based on this method a technique has been introduced to filter temporal sequences (e.g. aftershocks). Finally, a test has been developed for comparing different earthquake occurrence models. It has been found that the adaptive kernel estimation with temporal sequence filtering gives the best joint fit between the earthquake catalogue and the earthquake occurrence model, and between two earthquake occurrence models obtained from data from two independent time intervals. For the development of a geological earthquake occurrence model based on fault information, earthquake source relationships (i.e. rupture length versus rupture width scaling) have been revised. It has been found that large dip-slip and strike-slip earthquakes scale differently. Using these source relationships a dynamic stochastic fault model has been introduced. Whereas earthquake hazard studies often do not allow individual fault segments to produce compound ruptures, this model allows the linking of fault segments by chance. The moment release of simulated fault ruptures has been compared with the theoretical deformation along the plate boundary. When comparing the seismological and the geological earthquake occurrence model, it has been found that a 'good' occurrence model for large dip-slip earthquakes is given by the seismological occurrence model using the Gutenberg-Richter magnitude frequency distribution. In contrast, regions dominated by long strike-slip faults produce large earthquakes but not many small earthquakes and the occurrence of earthquakes on such faults should be inferred from the dynamic fault model.</p>

A shock-capturing SPH scheme based on adaptive kernel estimation

2006 ◽  
Vol 212 (1) ◽  
pp. 124-149 ◽  
Author(s):  
Leonardo Di G. Sigalotti ◽  
Hender López ◽  
Arnaldo Donoso ◽  
Eloy Sira ◽  
Jaime Klapp
Keyword(s):  
Kernel Estimation ◽  
Shock Capturing ◽  
Adaptive Kernel

scholarly journals Adaptive Kernel Estimation of the Conditional Quantiles

2015 ◽  
Vol 5 (1) ◽  
pp. 79
Author(s):  
Raid B. Salha ◽  
Hazem I. El Shekh Ahmed ◽  
Hossam O. EL-Sayed
Keyword(s):  
Distribution Function ◽  
Conditional Distribution ◽  
Mean Squared Error ◽  
Kernel Estimation ◽  
Conditional Quantiles ◽  
Squared Error ◽  
Adaptive Kernel ◽  
The Mean ◽  
Bias Variance ◽  
Kernel Estimations

In this paper, we define the adaptive kernel estimation of the conditional distribution function (cdf) for independent and identically distributed (iid) data using varying bandwidth. The bias, variance and the mean squared error of the proposed estimator are investigated. Moreover, the asymptotic normality of the proposed estimator is investigated.<br /><br />The results of the simulation study show that the adaptive kernel estimation of the conditional quantiles with varying bandwidth have better performance than the kernel estimations with fixed bandwidth.

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