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CSDA
2007
127views more  CSDA 2007»
13 years 6 months ago
Computing the least quartile difference estimator in the plane
A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robus...
Thorsten Bernholt, Robin Nunkesser, Karen Schettli...
NECO
2002
100views more  NECO 2002»
13 years 6 months ago
Robust Regression with Asymmetric Heavy-Tail Noise Distributions
In the presence of a heavy-tail noise distribution, regression becomes much more di cult. Traditional robust regression methods assume that the noise distribution is symmetric and...
Ichiro Takeuchi, Yoshua Bengio, Takafumi Kanamori
LOCA
2009
Springer
14 years 29 days ago
Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering
This paper presents two algorithms, non-linear regression and Kalman filtering, that fuse heterogeneous data (pseudorange and angle-of-arrival) from an ultra-wideband positioning ...
Kavitha Muthukrishnan, Mike Hazas
JEI
2010
123views more  JEI 2010»
13 years 1 months ago
Estimating reflectance from multispectral camera responses based on partial least-squares regression
Abstract. In multispectral imaging systems, the accuracy of reflectance estimation can be degraded by the nonlinearity in imaging process, which is due to non-Gaussian distribution...
Hui-Liang Shen, Hui-Jiang Wan, Zhe-Chao Zhang