Results 221 to 230 of about 20,217 (261)

A nonparametric bootstrap method for spatial data

Computational Statistics & Data Analysis, 2019
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Sergio Castillo-Páez, Rubén Fernández-Casal, Pilar García-Soidán   +2 more
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A NONPARAMETRIC BOOTSTRAP TEST OF CONDITIONAL DISTRIBUTIONS

Econometric Theory, 2006
Summary: This paper proposes a bootstrap test for the correct specification of parametric conditional distributions. It extends \textit{J. X. Zheng}'s test [ibid. 16, No. 5, 667--691 (2000; Zbl 0967.62032)] to allow for discrete dependent variables and for mixed discrete and continuous conditional variables.
Fan, Yanqin, Li, Qi, Min, Insik
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Bootstrapping nonparametric estimators of the volatility function

Journal of Econometrics, 2004
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Franke, Jürgen, Neumann, Michael H., Stockis, Jean-Pierre   +2 more
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The Nonparametric Bootstrap

2016
This chapter introduces Efron’s nonparametric bootstrap, with applications to linear statistics, and semi-linear regression due to Bickel and Freedman.
Rabi Bhattacharya, Lizhen Lin, Victor Patrangenaru   +2 more
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Bootstrap Methods in Nonparametric Regression

1991
Bootstrap techniques naturally arise in the setting of nonparametric regression when we consider questions of smoothing parameter selection or error bar construction. The bootstrap provides a simple-to-implement alternative to procedures based on asymptotic arguments.
Mammen, Enno, Härdle, Wolfgang
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Nonparametric bootstrapping for hierarchical data

Journal of Applied Statistics, 2010
Nonparametric bootstrapping for hierarchical data is relatively underdeveloped and not straightforward: certainly it does not make sense to use simple nonparametric resampling, which treats all observations as independent. We have provided some resampling strategies of hierarchical data, proved that the strategy of nonparametric bootstrapping on the ...
Shiquan Ren, Hong Lai, Wenjing Tong, Mostafa Aminzadeh, Xuezhang Hou, Shenghan Lai   +5 more
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A wild bootstrap approach for nonparametric repeated measurements

Computational Statistics & Data Analysis, 2017
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Sarah Friedrich, Frank Konietschke, Markus Pauly   +2 more
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Parametric and nonparametric bootstrap methods for meta-analysis

Behavior Research Methods, 2005
In a meta-analysis, the unknown parameters are often estimated using maximum likelihood, and inferences are based on asymptotic theory. It is assumed that, conditional on study characteristics included in the model, the between-study distribution and the sampling distributions of the effect sizes are normal.
Wim, Van Den Noortgate, Patrick, Onghena
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Nonparametric Markov chain bootstrap for multiple imputation

Computational Statistics & Data Analysis, 2004
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Bootstrap Initialization of Nonparametric Texture Models for Tracking

2000
In bootstrap initialization for tracking, we exploit a weak prior model used to track a target to learn a stronger model, without manual intervention. We define a general formulation of this problem and present a simple taxonomy of such tasks. The formulation is instantiated with algorithms for bootstrap initialization in two domains: In one, the ...
Kentaro Toyama, Ying Wu 0001
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