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Pseudo-Ranks: How to Calculate Them Efficiently in R
Journal of Statistical Software, 2020 Many popular nonparametric inferential methods are based on ranks. Among the most commonly used and most famous tests are for example the Wilcoxon-Mann-Whitney test for two independent samples, and the Kruskal-Wallis test for multiple independent groups.
Martin Happ +3 more
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Nonparametric Statistical Methods
, 2010 Nonparametric methods are appropriate when certain assumptions about distributions that common parametric methods make are questionable. In this entry, we review nonparametric statistical tests based on exact or simulated sampling distributions. We also discuss methods for nonparametric data exploration and nonparametric regression and we explain ...
Sijtsma, K., Emons, W.H.M.
openaire +3 more sources
Uniform Consistency for Functional Conditional U-Statistics Using Delta-Sequences
Mathematics, 2022 U-statistics are a fundamental class of statistics derived from modeling quantities of interest characterized by responses from multiple subjects. U-statistics make generalizations the empirical mean of a random variable X to the sum of all k-tuples of X
Salim Bouzebda, Amel Nezzal, Tarek Zari
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Nonparametric regression in exponential families [PDF]
, 2010 Most results in nonparametric regression theory are developed only for the case of additive noise. In such a setting many smoothing techniques including wavelet thresholding methods have been developed and shown to be highly adaptive.
Brown, Lawrence D. +2 more
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Penalized variable selection procedure for Cox models with semiparametric relative risk
, 2010 We study the Cox models with semiparametric relative risk, which can be partially linear with one nonparametric component, or multiple additive or nonadditive nonparametric components.
Du, Pang, Liang, Hua, Ma, Shuangge
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Genetics and Molecular Biology, 2008 Evaluation of performance stability and high yield is essential for yield trials conducted in different environments. We determined the stability of 10 bread wheat (Triticum aestivum L.) genotypes (5 cultivars and 5 advanced lines) using nonparametric ...
Mevlut Akcura, Yuksel Kaya
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Specification testing in nonlinear and nonstationary time series autoregression
, 2009 This paper considers a class of nonparametric autoregressive models with nonstationarity. We propose a nonparametric kernel test for the conditional mean and then establish an asymptotic distribution of the proposed test. Both the setting and the results
Gao, Jiti +3 more
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A Class of Enhanced Nonparametric Control Schemes Based on Order Statistics and Runs
Stats, 2023 In this article, we establish a new class of nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules.
Nikolaos I. Panayiotou +1 more
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Nonparametric regression with homogeneous group testing data
, 2012 We introduce new nonparametric predictors for homogeneous pooled data in the context of group testing for rare abnormalities and show that they achieve optimal rates of convergence.
Delaigle, Aurore, Hall, Peter
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Asymptotically Sufficient Statistics in Nonparametric Regression Experiments with Correlated Noise
Journal of Probability and Statistics, 2009 We find asymptotically sufficient statistics that could help simplify inference in nonparametric regression problems with correlated errors. These statistics are derived from a wavelet decomposition that is used to whiten the noise process and to ...
Andrew V. Carter
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