Adaptive Kernel Density Estimation
By Philippe Van Kerm. 2003
118 citations recorded by the source corpus.
Subfields: Applied Mathematics, Control and Systems Engineering, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/b537ded0283ec2b132b3738aa17eac00ce44a21c
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In Applied Mathematics
In Control and Systems Engineering
In Statistics and Probability
Citations in the corpus
- IsoplotR: A free and open toolbox for geochronology (2018, unknown): “…approach of Abramson (1982), whereby: hi ¼ h ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi G=kdeðtiÞ q in which kde(ti) is the ‘pilot density’ using a fixed bandwidth (h) evaluated at ti, and G is the geometric mean of the pilot density over all the sample points (Van Kerm, 2003).”
- Home range, activity and sociality of a top predator, the dingo: a test of the Resource Dispersion Hypothesis (2013, methodology): “As opposed to the adaptive kernel (which adapts to the sparseness of data by using a broader kernel (Van Kerm 2003)), the fixed kernel is more stable for defining probability contours of 80% (Verdolin 2009), so the latter was used.”
- A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions (2011, unknown): “If k1d=li is query adaptive, the resulting function would not integrate to 1 andwould notmeet the definition of a PDF (Sain, 1994).”