1,993 research outputs found
Splines and Wavelets on Geophysically Relevant Manifolds
Analysis on the unit sphere found many applications in
seismology, weather prediction, astrophysics, signal analysis, crystallography,
computer vision, computerized tomography, neuroscience, and statistics.
In the last two decades, the importance of these and other applications
triggered the development of various tools such as splines and wavelet bases
suitable for the unit spheres , and the
rotation group . Present paper is a summary of some of results of the
author and his collaborators on generalized (average) variational splines and
localized frames (wavelets) on compact Riemannian manifolds. The results are
illustrated by applications to Radon-type transforms on and
.Comment: The final publication is available at http://www.springerlink.co
The Empirical Beta Copula
Given a sample from a multivariate distribution , the uniform random
variates generated independently and rearranged in the order specified by the
componentwise ranks of the original sample look like a sample from the copula
of . This idea can be regarded as a variant on Baker's [J. Multivariate
Anal. 99 (2008) 2312--2327] copula construction and leads to the definition of
the empirical beta copula. The latter turns out to be a particular case of the
empirical Bernstein copula, the degrees of all Bernstein polynomials being
equal to the sample size.
Necessary and sufficient conditions are given for a Bernstein polynomial to
be a copula. These imply that the empirical beta copula is a genuine copula.
Furthermore, the empirical process based on the empirical Bernstein copula is
shown to be asymptotically the same as the ordinary empirical copula process
under assumptions which are significantly weaker than those given in Janssen,
Swanepoel and Veraverbeke [J. Stat. Plan. Infer. 142 (2012) 1189--1197].
A Monte Carlo simulation study shows that the empirical beta copula
outperforms the empirical copula and the empirical checkerboard copula in terms
of both bias and variance. Compared with the empirical Bernstein copula with
the smoothing rate suggested by Janssen et al., its finite-sample performance
is still significantly better in several cases, especially in terms of bias.Comment: 23 pages, 3 figure
Ellipse-preserving Hermite interpolation and subdivision
We introduce a family of piecewise-exponential functions that have the
Hermite interpolation property. Our design is motivated by the search for an
effective scheme for the joint interpolation of points and associated tangents
on a curve with the ability to perfectly reproduce ellipses. We prove that the
proposed Hermite functions form a Riesz basis and that they reproduce
prescribed exponential polynomials. We present a method based on Green's
functions to unravel their multi-resolution and approximation-theoretic
properties. Finally, we derive the corresponding vector and scalar subdivision
schemes, which lend themselves to a fast implementation. The proposed vector
scheme is interpolatory and level-dependent, but its asymptotic behaviour is
the same as the classical cubic Hermite spline algorithm. The same convergence
properties---i.e., fourth order of approximation---are hence ensured
Introducing Mexican needlets for CMB analysis: Issues for practical applications and comparison with standard needlets
Over the last few years, needlets have a emerged as a useful tool for the
analysis of Cosmic Microwave Background (CMB) data. Our aim in this paper is
first to introduce in the CMB literature a different form of needlets, known as
Mexican needlets, first discussed in the mathematical literature by Geller and
Mayeli (2009a,b). We then proceed with an extensive study of the properties of
both standard and Mexican needlets; these properties depend on some parameters
which can be tuned in order to optimize the performance for a given
application. Our second aim in this paper is then to give practical advice on
how to adjust these parameters in order to achieve the best properties for a
given problem in CMB data analysis. In particular we investigate localization
properties in real and harmonic spaces and propose a recipe on how to quantify
the influence of galactic and point source masks on the needlet coefficients.
We also show that for certain parameter values, the Mexican needlets provide a
close approximation to the Spherical Mexican Hat Wavelets (whence their name),
with some advantages concerning their numerical implementation and the
derivation of their statistical properties.Comment: 40 pages, 11 figures, published version, main modification: added
section on more realistic galactic and point source mask
Metric entropy, n-widths, and sampling of functions on manifolds
We first investigate on the asymptotics of the Kolmogorov metric entropy and
nonlinear n-widths of approximation spaces on some function classes on
manifolds and quasi-metric measure spaces. Secondly, we develop constructive
algorithms to represent those functions within a prescribed accuracy. The
constructions can be based on either spectral information or scattered samples
of the target function. Our algorithmic scheme is asymptotically optimal in the
sense of nonlinear n-widths and asymptotically optimal up to a logarithmic
factor with respect to the metric entropy
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