Search results for "Nonparametric statistics"
showing 10 items of 80 documents
Multivariate nonparametric tests in a randomized complete block design
2003
AbstractIn this paper multivariate extensions of the Friedman and Page tests for the comparison of several treatments are introduced. Related unadjusted and adjusted treatment effect estimates for the multivariate response variable are also found and their properties discussed. The test statistics and estimates are analogous to the traditional univariate methods. In test constructions, the univariate ranks are replaced by multivariate spatial ranks (J. Nonparam. Statist. 5 (1995) 201). Asymptotic theory is developed to provide approximations for the limiting distributions of the test statistics and estimates. Limiting efficiencies of the tests and treatment effect estimates are found in the…
Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression
2016
In Hettmansperger and Randles (Biometrika 89:851–860, 2002) spatial sign vectors were used to derive simultaneous estimators of multivariate location and shape. Oja (Multivariate nonparametric methods with R. Springer, New York, 2010) proposed a similar approach for the multivariate linear regression case. These estimators are highly robust and have under general assumptions a joint limiting multinormal distribution. The estimates are easy to compute using fixed-point algorithms. There are however no exact proofs for the convergence of these algorithms. The existence and uniqueness of the solutions also still remain unproven although we believe that they hold under general conditions. To ci…
Non-Parametric Rank Statistics for Spectral Power and Coherence
2019
AbstractDespite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/c…
Non-parametric spectrum cartography using adaptive radial basis functions
2017
This paper presents a framework for spectrum cartography based on the use of adaptive Gaussian radial basis functions (RBF) centered around a specific number of centroid locations, which are determined, jointly with the other RBF parameters, by the available measurement values at given sensor locations in a specific geographical area. The spectrum map is constructed non-parametrically as no prior knowledge about the transmitters is assumed. The received signal power at each location (over a given bandwidth and time period) is estimated as a weighted contribution from different RBF, in such a way that the both RBF parameters and the weights are jointly optimized using an alternating minimiza…
Visual aftereffects and sensory nonlinearities from a single statistical framework
2015
When adapted to a particular scenery our senses may fool us: colors are misinterpreted, certain spatial patterns seem to fade out, and static objects appear to move in reverse. A mere empirical description of the mechanisms tuned to color, texture, and motion may tell us where these visual illusions come from. However, such empirical models of gain control do not explain why these mechanisms work in this apparently dysfunctional manner. Current normative explanations of aftereffects based on scene statistics derive gain changes by (1) invoking decorrelation and linear manifold matching/equalization, or (2) using nonlinear divisive normalization obtained from parametric scene models. These p…
SM identification of approximating models forH∞ robust control
1999
Set Membership (SM) W, identification of mixed parametric and nonparametric models is investigated, aimed to estimate a low order approximating model and an identification error, giving a measure of the unmodeled dynamics in a form well suited for H, control methodologies. In particular, the problem of estimating the parameters of the parametric part and the H, bound on the modeling error is solved using frequency domain data, supposing lbo bounded measurement errors and exponentially stable unmodeled dynamics. The effectiveness of the proposed procedure is tested on some numerical examples, showing the advantages of the proposed methods over the existing nonparametric H, identification app…
I: Boxplots - die flexible Alternative zum „Antennenbildchen”
2002
Data description for continuous parameters is sometimes only based on means and standard deviations of measurement series, graphical representation only concentrates on corresponding "MSE plots", which provide means and standard deviations or even only mean squared errors. However, this strategy is only correct for normally distributed data. Outliers may seriously bias mean and standard deviations and may therefore lead to wrong clinical conclusions. The present paper suggests the use of medians and quartiles, which - just like their graphical pendant, the nonparametric "box whisker plot" - can be applied much more flexibly.
A statistical study of the quality of surface water intended for human consumption near Valencia (Spain)
2007
Water quality in the European Union is subject to legislation through directives that are applicable in all Member States. The directives specify a set of physical and chemical parameters that should be regularly controlled using a network of sampling points, with sampling based on the intended use of the water. This paper presents the results of a statistical comparison of the quality of water intended for human consumption at two different locations (the Canal de Benagéber and the Canal Júcar-Turia) near the town of Valencia (Spain). These are currently the only canals that could supply Valencia and other nearby towns with drinking water. The parameters considered in this paper are the on…
Empirical Estimation of Accumulation-Induced Change in Gill Net Catchability: Mind the Observation Errors
2015
We analyzed cumulative catches for 24 h gill net exposures divided into 4*6 h, 2*12 h and 1*24 h soak time treatments to estimate the reduction in its catchability due to accumulation of fish. The effects of loss of catch during net lifting, disturbance effect and fouling were eliminated as far as possible to reveal the true effect of accumulation. First we applied simple nonparametric and parametric tests in comparison of treatments. As expected, considerable reduction in catchability took place along with the increase in soak time, indicated by significantly lower total 24 h catches from longer soaks in comparison with shorter ones. The reduction was more pronounced for roach than for per…
Adapted processing of catadioptric images using polarization imaging
2009
A non parametric method that defines a pixel neighborhood within catadioptric images is presented in this paper. It is based on an accurate modeling of the mirror shape by using polarization imaging. Unlike the most of current processing methods in the literature, this method is non-parametric and can deal with the deformation of catadioptric images. This paper demonstrates how an appropriate neighborhood can be derived from the polarization parameters by estimation of the degree of polarization and the angle of polarization which in return directly provide an adapted neighborhood of each pixel that can be used to perform image derivation, edge detection, interest point detection and namely…