A smoothed monotonic regression via L2 regularization
O Sysoev, O Burdakov - Knowledge and Information Systems, 2019 - Springer
Monotonic regression is a standard method for extracting a monotone function from non-
monotonic data, and it is used in many applications. However, a known drawback of this …
monotonic data, and it is used in many applications. However, a known drawback of this …
[PDF][PDF] A generalised PAV algorithm for monotonic regression in several variables
O Burdakov, A Grimvall, M Hussian - COMPSTAT, Proceedings of …, 2004 - researchgate.net
We present a new algorithm for monotonic regression in one or more explanatory variables.
Formally, our method generalises the well-known PAV (pool-adjacent-violators) algorithm …
Formally, our method generalises the well-known PAV (pool-adjacent-violators) algorithm …
A dual active-set algorithm for regularized monotonic regression
O Burdakov, O Sysoev - Journal of Optimization Theory and Applications, 2017 - Springer
Monotonic (isotonic) regression is a powerful tool used for solving a wide range of important
applied problems. One of its features, which poses a limitation on its use in some areas, is …
applied problems. One of its features, which poses a limitation on its use in some areas, is …
Data preordering in generalized PAV algorithm for monotonic regression
O Burdakov, A Grimvall, O Sysoev - Journal of Computational Mathematics, 2006 - JSTOR
Monotonic regression (MR) is a least distance problem with monotonicity constraints
induced by a partially ordered data set of observations. In our recent publication [In Ser …
induced by a partially ordered data set of observations. In our recent publication [In Ser …
[PDF][PDF] Monotonic regression for the detection of temporal trends in environmental quality data
M Hussian, A Grimvall, O Burdakov… - MATCH Commun. Math …, 2005 - academia.edu
Monotonic regression is a non-parametric method designed especially for applications in
which the expected value of a response variable increases or decreases in relation to one or …
which the expected value of a response variable increases or decreases in relation to one or …
Polynomial regression under shape constraints
F Wahl, T Espinasse - 2014 - inria.hal.science
Calculating regression under shape constraints is a problem addressed by statisticians
since long. This paper shows how to calculate a polynomial regression of any degree and of …
since long. This paper shows how to calculate a polynomial regression of any degree and of …
[PDF][PDF] Monotonic regression for assessment of trends in environmental quality data
M Hussian, A Grimvall, O Burdakov… - European Congress on …, 2004 - academia.edu
Monotonic regression is a non-parametric method that is designed especially for
applications in which the expected value of a response variable increases or decreases in …
applications in which the expected value of a response variable increases or decreases in …
[PDF][PDF] A simplified HDR image processing pipeline for digital photography
J Singnoo - 2012 - ueaeprints.uea.ac.uk
High Dynamic Range (HDR) imaging has revolutionized the digital imaging. It allows
capture, storage, manipulation, and display of full dynamic range of the captured scene. As a …
capture, storage, manipulation, and display of full dynamic range of the captured scene. As a …
[PDF][PDF] MONOTONIC REGRESSION FOR ASSESSMENT OF TRENDS IN ENVIRONMENTAL QUALITY DATA
Monotonic regression is a non-parametric method that is designed especially for
applications in which the expected value of a response variable increases or decreases in …
applications in which the expected value of a response variable increases or decreases in …