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Generalizing k-means for an arbitrary distance matrix
Generalizing k-means an arbitrary distance matrix
2013/5/2
The original k-means clustering method works only if the exact vectors representing the data points are known. Therefore calculating the distances from the centroids needs vector operations, since the...
First of all we want to thank the editor, Michael Newton, for leading the review and discussion of our work.
Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation...
The shortest distance in random multi-type intersection graphs
Intersection graph shortest path branching process approximation Poissonapproximation
2010/3/9
Using an associated branching process as the basis of our approximation, we
show that typical inter-point distances in a multitype random intersection graph
have a defective distribution, which is w...
Two members of an exponential family can be
represented as two points in the natural parameter space of that
family or as two points in the expectation parameter space. The
theorem describes a simp...
Minimizing L(1)-distance between distribution functions
Minimizing L(1)-distance distribution functions
2009/9/23
Minimizing L(1)-distance between distribution functions。
Minimum L(1)-penalized distance estimators of a density and its derivatives
Minimum L(1)-penalized distance estimators a density derivatives
2009/9/23
Minimum L(1)-penalized distance estimators of a density and its derivatives。
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
Random Sets Boundaries Oriented Distance Functions
2010/3/18
Shape estimation and object reconstruction are common problems in image analysis. Mathematically,viewing objects in the image plane as random sets reduces the problem of shape estimation to inference ...
Minimum distance regression model checking with Berkson measurement errors
Kernel estimator L2 distance consistency local alternatives
2010/3/18
Lack-of-fit testing of a regression model with Berkson measurement
error has not been discussed in the literature to date. To fill
this void, we propose a class of tests based on minimized integrate...