搜索结果: 1-12 共查到“统计学 nearest-neighbor”相关记录12条 . 查询时间(0.16 秒)
Non-nearest-neighbor interactions in nonlinear dynamical lattices
Discrete nonlinear schrodinger equation the nonlinear dynamic systematic zero coupling
2014/12/24
We revisit the theme of non-nearest-neighbor interactions in nonlinear dynamical lattices, in the prototypical setting of the discrete nonlinear Schrödinger equation. Our approach offers a system...
k-Nearest neighbor density estimation on Riemannian Manifolds
Asymptotic results Density estimation Meteorological applications
2011/7/6
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belong in a Riemannian manifolds.
Pruning nearest neighbor cluster trees
cluster trees cluster structure subgraphs of a k-NN graph
2011/6/16
Nearest neighbor (k-NN) graphs are widely used
in machine learning and data mining applications,
and our aim is to better understand what
they reveal about the cluster structure of the unknown
und...
Rates of convergence for nearest neighbor estimators with the smoother regression function
Regression Nonparametric estimation Nearest neighbor Rate of conver-gence
2011/3/25
In regression analysis one wants to estimate the regression function from a data. In this paper we consider the rate of convergence for the nearest neighbor estimator in case that the regression funct...
Statistical analysis of $k$-nearest neighbor collaborative recommendation
Collaborative recommendation cosine-type similarity
2010/10/14
Collaborative recommendation is an information-filtering technique that attempts to present information items that are likely of interest to an Internet user. Traditionally, collaborative systems deal...
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
Rényi Entropy Mutual Information Generalized Nearest-Neighbor Graphs
2010/3/11
In this paper we consider simple and computationally efficient nonparametric estimators of R´enyi
entropy and mutual information based on an i.i.d. sample drawn from an unknown, absolutely
con...
New Tests of Spatial Segregation Based on Nearest Neighbor Contingency Tables
Association spatial clustering complete spatial randomness independence nearest neighbor methods
2010/4/30
The spatial clustering of points from two or more classes (or species) has important implications in many fields and may cause the spatial patterns of segregation and association, which are two major ...
On fractional Brownian motion limits in one dimensional nearest-neighbor symmetric simple exclusion
Simple exclusion nearest-neighbor one dimensional tagged particle
2009/6/12
The purpose of this note is to improve this convergence to a functional central
limit theorem,with respect to the uniform topology,and so complete the solution
to a conjecture in the literature with...
Orthogonality and probability: beyond nearest neighbor transitions
reversible Markov chains orthogonal polynomials Karlin-McGregor representation
2009/4/29
In this article, we will explore why Karlin-McGregor method of using orthogonal polynomials in the study of Markov processes was so successful for one dimensional nearest neighbor processes, but faile...
Orthogonality and probability: beyond nearest neighbor transitions
beyond nearest Orthogonality
2009/4/22
In this article, we will explore why Karlin-McGregor method of using orthogonal polynomials in the study of Markov processes was so successful for one dimensional nearest neighbor processes, but faile...
Directional Clustering Tests Based on Nearest Neighbor Contingency Tables
Association clustering complete spatial randomness independence random labeling spatialpattern
2010/3/18
Spatial interaction between two or more classes or species has important implications in various fields and causes multivariate patterns such as segregation or association. Segregation occurs when mem...
Metric Embedding for Nearest Neighbor Classification
Metric Embedding Nearest Neighbor Classification
2010/4/29
The distance metric plays an important role in nearest neighbor (NN) classification. Usually
the Euclidean distance metric is assumed or a Mahalanobis distance metric is optimized
to improve the NN ...