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A Projection Approach to Monotonic Regression with Bernstein Polynomials

Journal of Systems Science and Complexity, 2022
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Xiangzhong Fang
exaly   +3 more sources

Monotone Regrouping, Regression, and Simpson's Paradox [PDF]

The American Statistician, 2003
This article shows in a general setup that if data Y are grouped by a covariate X in a certain way, then under a condition of monotone regression of Y on X, a Simpson's type paradox is natural rather than surprising. This model was motivated by an observation on recent SAT data which are presented.
Rinott Y., Tam M.
openaire   +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
openaire   +1 more source

About monotone regression quantiles

Statistics & Probability Letters, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source