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» Smooth functions and local extreme values
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CSDA
2007
102views more  CSDA 2007»
13 years 3 months ago
Smooth functions and local extreme values
Given a sample of n observations y1, . . . , yn at time points t1, . . . , tn we consider the problem of specifying a function ˜f such that ˜f • is smooth, • fits the data ...
A. Kovac
BMCBI
2008
149views more  BMCBI 2008»
13 years 3 months ago
Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment s
Background: Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic d...
Olivier Bastien, Eric Maréchal
JGO
2010
531views more  JGO 2010»
13 years 2 months ago
Characterizing zero-derivative points
We study smooth functions in several variables with a Lipschitz derivative. It is shown that these functions have the “envelope property”: Around zero-derivative points, and on...
Sanjo Zlobec
IROS
2007
IEEE
90views Robotics» more  IROS 2007»
13 years 10 months ago
Improved likelihood models for probabilistic localization based on range scans
— Range sensors are popular for localization since they directly measure the geometry of the local environment. Another distinct benefit is their typically high accuracy and spa...
Patrick Pfaff, Christian Plagemann, Wolfram Burgar...
SAC
2002
ACM
13 years 3 months ago
Choice of wavelet smoothness, primary resolution and threshold in wavelet shrinkage
This article introduces a fast cross-validation algorithm that performs wavelet shrinkage on data sets of arbitrary size and irregular design and also simultaneously selects good ...
Guy P. Nason