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AMC
2005
106views more  AMC 2005»
13 years 4 months ago
The least squares type estimation of the parameters in the power hazard function
The power hazard function is defined by h(t) = atk . In this investigation, we use the least squares type estimation to estimate the parameter a when k is known, the parameter k w...
A. R. Mugdadi
CSDA
2006
145views more  CSDA 2006»
13 years 4 months ago
Improved predictions penalizing both slope and curvature in additive models
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Magne Aldrin
BMCBI
2007
182views more  BMCBI 2007»
13 years 5 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
CGF
2011
12 years 8 months ago
Estimating Color and Texture Parameters for Vector Graphics
Diffusion curves are a powerful vector graphic representation that stores an image as a set of 2D Bezier curves with colors defined on either side. These colors are diffused over...
Stefan Jeschke, David Cline, Peter Wonka
ESANN
2004
13 years 6 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...