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Discovering the ecological structure of different macrophyte groups in rivers using non-parametric and parametric multivariate ordination techniques. [PDF]

Sci Rep
Budka A, Szoszkiewicz K, Pietruczuk K, Agaj T.   +3 more
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On a non-parametric test

, 1952
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A Non-parametric Fisher Kernel

2021
In this manuscript, we derive a non-parametric version of the Fisher kernel. We obtain this original result from the Non-negative Matrix Factorization with the Kullback-Leibler divergence. By imposing suitable normalization conditions on the obtained factorization, it can be assimilated to a mixture of densities, with no assumptions on the distribution
Pau Figuera, Pablo García Bringas
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Non-Parametric Regression Methods

Computational Management Science, 2006
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Non-Parametric Analysis of Covariance

Biometrics, 1995
An analysis of covariance model where the covariate effect is assumed only to be smooth is considered. The possibility of different shapes of covariate effect in different groups is also allowed and tests of equality and of parallelism across groups are constructed.
Young, Stuart G., Bowman, Adrian W.
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Non-parametric estimates of overlap

Statistics in Medicine, 2001
Kernel densities provide accurate non-parametric estimates of the overlapping coefficient or the proportion of similar responses (PSR) in two populations. Non-parametric estimates avoid strong assumptions on the shape of the populations, such as normality or equal variance, and possess sampling variation approaching that of parametric estimates.
R A, Stine, J F, Heyse
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Non-parametric self-calibration

Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005
In this paper, we develop a theory of non-parametric self-calibration. Recently, schemes have been devised for non-parametric laboratory calibration, but not for self-calibration. We allow an arbitrary warp to model the intrinsic mapping, with the only restriction that the camera is central and that the intrinsic mapping has a well-defined non-singular
David Nistér, Henrik Stewénius, Etienne Grossmann   +2 more
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Non-Parametric Subject Prediction

2019
Automatic subject prediction is a desirable feature for modern digital library systems, as manual indexing can no longer cope with the rapid growth of digital collections. This is an “extreme multi-label classification” problem, where the objective is to assign a small subset of the most relevant subjects from an extremely large label set.
Shenghui Wang 0001, Rob Koopman, Gwenn Englebienne   +2 more
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Non‐parametric Regression for Circular Responses

Scandinavian Journal of Statistics, 2012
Abstract.Regression with a circular response is a topic of current interest. We introduce non‐parametric smoothing for this problem. Simple adaptations of a weight function enable a unified formulation for both real‐line and circular predictors, whereas these cases have been tackled by quite distinct parametric methods. Additionally, we discuss various
MARCO DI MARZIO, PANZERA, AGNESE, CHARLES C. TAYLOR   +2 more
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