Fast Computation of Kernel Estimators
نویسندگان
چکیده
منابع مشابه
Fast Computation of Kernel Estimators
The computational complexity of evaluating the kernel density estimate (or its derivatives) at m evaluation points given n sample points scales quadratically as O(nm)–making it prohibitively expensive for large data sets. While approximate methods like binning could speed up the computation they lack a precise control over the accuracy of the approximation. There is no straightforward way of ch...
متن کاملFast Computation of Subpath Kernel for Trees
The kernel method is a popular approach to analyzing structured data such as sequences, trees, and graphs; however, unordered trees have not been investigated extensively. Kimura et al. (2011) proposed a kernel function for unordered trees on the basis of their subpaths, which are vertical substructures of trees responsible for hierarchical information in them. Their kernel exhibits practically...
متن کاملFast computation of geometric moments using a symmetric kernel
This paper presents a novel set of geometric moments with symmetric kernel (SGM) obtained using an appropriate transformation of image coordinates. By using this image transformation, the computational complexity of geometric moments (GM) is reduced significantly through the embedded symmetry and separability properties. In addition, it minimizes the numerical instability problem that occurs in...
متن کاملSimple Kernel Estimators for
We consider deconvolution problems where the observations are equal in distribution to Here the random variables in the sums are independent, the E i are exponentially distributed, the L i are Laplace distributed and Y has an unknown distribution F which we want to estimate. The constants i or i are given. These problems include exponential, gamma and Laplace deconvolution. We derive inversion ...
متن کاملDeconvoluting Kernel Density Estimators
This paper considers estimation of a continuous bounded probability density when observations from the density are contaminated by additive measurement errors having a known distribution. Properties of the estimator obtained by deconvolving a kernel estimator of the observed data are investigated. When the kernel used is sufficiently smooth the deconvolved estimator is shown to be pointwise con...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2010
ISSN: 1061-8600,1537-2715
DOI: 10.1198/jcgs.2010.09046