Results 271 to 280 of about 46,298 (299)

Nonparametric Estimation and Hypothesis Testing in Econometric Models

Empirical Economics, 1988
In this paper we systematically review and develop nonparametric estimation and testing techniques in the context of econometric models. The results are discussed under the settings of regression model and kernel estimation, although as indicated in the paper these results can go through for other econometric models and for the nearest neighbor ...
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Nonparametric Hypothesis Testing with Parametric Rates of Convergence

International Economic Review, 1991
Nonparametric estimators are frequently criticized for their poor performance in small samples. In this paper, the author considers using kernel methods for the estimation of the expected derivatives of a regression function. The proposed estimators are shown to be asymptotically normal and n-consistent.
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A General Approach to Hypothesis Testing for Nonparametric Tests

The Journal of Experimental Education, 1990
Researchers have preferred normal-theory tests over nonparametric procedures, despite evidence that the statistical properties of the latter are sometimes superior for variables and subject populations frequently encountered in educational and psychological research.
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Support Vector Machine for Nonparametric Binary Hypothesis Testing

1999
The Support Vector Machine, introduced in [1] as a practical implementation of the principle of structural risk minimization, constitutes one of the most promising methods for constructing a mathematical model only on the base of a limited amount of measured data. In this paper, we consider the application of this method to the problem of nonparametric
MATTERA D., PALMIERI, Francesco
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Adaptive and spatially adaptive testing of a nonparametric hypothesis

1996
Preprint: Weierstraß-Institut für Angewandte Analysis und Stochastik, vol ...
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A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING [PDF]

, 2001
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test.
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Bayesian nonparametric hypothesis testing

In this thesis, we propose novel Bayesian Nonparametric hypothesis testing procedures for correlated data. First, we develop and study a proposal for comparing the distributions of paired samples. Next, we propose and analyze a hypothesis testing procedure for longitudinal data analysis.
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Multiple Hypothesis Testing-Based Cepstrum Thresholding for Nonparametric Spectral Estimation

IEEE Signal Processing Letters, 2022
Prabhu Babu, Petre Stoica
exaly  

Nonparametric Inference for Spatiotemporal Data Based on Local Null Hypothesis Testing for Functional Data

Wiley Series in Probability and Statistics, 2022
Alessia Pini, Simone Vantini
exaly  

Nonparametric pragmatic hypothesis testing

2022
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