Results 221 to 230 of about 4,642 (256)

Primal-Dual Monotone Kernel Regression

Neural Processing Letters, 2005
This paper considers the estimation of monotone nonlinear regression functions based on Support Vector Machines (SVMs), Least Squares SVMs (LS-SVMs) and other kernel machines. It illustrates how to employ the primal-dual optimization framework characterizing LS-SVMs in order to derive a globally optimal one-stage estimator for monotone regression. As a
Johan Suykens, K Pelckmans
exaly   +2 more sources

Windowed locally monotonic regression

[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991
Lomotonicity, the largest degree of local monotonicity that a signal has, is proposed as an appropriate measure of smoothness when studying smoothers such as the median filter. Locally monotonic regression (LMR) optimally solves the problem of smoothing a signal to a specified minimal degree of lomotonicity, but it often requires an excess of ...
Alfredo Restrepo Palacios, Alan C. Bovik
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About monotone regression quantiles

Statistics & Probability Letters, 2000
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Poiraud-Casanova, Sandrine, Thomas-Agnan, Christine   +1 more
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Testing Monotonicity of Regression

Journal of Computational and Graphical Statistics, 1998
Abstract This article provides a test of monotonicity of a regression function. The test is based on the size of a “critical” bandwidth, the amount of smoothing necessary to force a nonparametric regression estimate to be monotone. It is analogous to Silverman's test of multimodality in density estimation.
A. W. Bowman, M. C. Jones, I. Gijbels
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A Method for Bayesian Monotonic Multiple Regression

Scandinavian Journal of Statistics, 2010
Abstract.  When applicable, an assumed monotonicity property of the regression function w.r.t. covariates has a strong stabilizing effect on the estimates. Because of this, other parametric or structural assumptions may not be needed at all. Although monotonic regression in one dimension is well studied, the question remains whether one can find ...
Saarela, Olli, Arjas, Elja
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A Projection Approach to Monotonic Regression with Bernstein Polynomials

Journal of Systems Science and Complexity, 2022
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Guo Zhu, Xiangzhong Fang
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Monotone Nonparametric Regression and Confidence Intervals

Communications in Statistics - Simulation and Computation, 2010
Several variations of monotone nonparametric regression have been developed over the past 30 years. One approach is to first apply nonparametric regression to data and then monotone smooth the initial estimates to “iron out” violations to the assumed order.
Matthew Strand, Yu Zhang, Bruce J. Swihart   +2 more
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Inverse boosting for monotone regression functions

Computational Statistics & Data Analysis, 2005
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Yuwon Kim, Ja-Yong Koo
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On the statistical optimality of locally monotonic regression

IEEE Transactions on Signal Processing, 1994
Locally monotonic regression is a recently proposed technique for the deterministic smoothing of finite-length discrete signals under the smoothing criterion of local monotonicity. Locally monotonic regression falls within a general framework for the processing of signals that may be characterized in three ways: regressions are given by projections ...
Alfredo Restrepo Palacios, Alan C. Bovik
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Non-Euclidean locally monotonic regression

International Conference on Acoustics, Speech, and Signal Processing, 2002
The concept of locally monotonic regression is extended by considering metrics on r/sup n/ that are different from the Euclidean metric. The existence of regressions for a large class of metrics is shown. Algorithms that show the computability of locally monotonic regressions are given.
Alfredo Restrepo Palacios, Irwin W. Sandberg, Alan C. Bovik   +2 more
openaire   +1 more source