Results 271 to 280 of about 4,338,901 (297)

A Parametric Copula-Based Framework for Hypothesis Testing Using Heterogeneous Data

IEEE Transactions on Signal Processing, 2011
We present a parametric framework for the joint processing of heterogeneous data, specifically for a binary classification problem. Processing such a data set is not straightforward as heterogeneous data may not be commensurate. In addition, the signals may also exhibit statistical dependence due to overlapping fields of view. We propose a copula-based
Satish G. Iyengar, Pramod K. Varshney, Thyagaraju R. Damarla   +2 more
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Non-parametric hypothesis testing procedures and applications to demand analysis

Journal of Econometrics, 1985
This paper proposes a hypothesis test that a (possibly vector-valued) regression function g lies in a particular family of functions \({\mathcal F}\), not necessarily a finite-dimensional parametric family, where \({\mathcal F}\) is a compact subset of an appropriate topological space of continuous functions.
Epstein, Larry G., Yatchew, Adonis J.
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Non-parametric multivariate regression hypothesis testing

2012
We introduce three nonparametric multivariate methods for testing the elements of the regression matrix. We investigate the nite-sample performance, robustness and heteroscedasticity of these methods. Our simulation results show that Method 1 performs well when the error term has a non-Gaussian distribution and there is homoscedasticity.
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Hypothesis Formulation and Testing – Parametric Tests

2021
R. Russell Rhinehart, Robert M. Bethea
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Basic Concept of Hypothesis Testing and Parametric Test

2022
Basant Kumar Das, Dharm Nath Jha, Sanjeev Kumar Sahu, Anil Kumar Yadav, Rohan Kumar Raman, M. Kartikeyan   +5 more
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A predictive motivation for loss function specification in parametric hypothesis testing

Economics Letters, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On Parametric Hypothesis Testing with Non-Parametric Tests

Theory of Probability & Its Applications, 1970
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Analysis of type I and II error rates of Bayesian and frequentist parametric and nonparametric two-sample hypothesis tests under preliminary assessment of normality

Computational Statistics, 2020
Riko Kelter
exaly  

Hypothesis testing for two population means: parametric or non-parametric test?

Journal of Statistical Computation and Simulation, 2020
Michail Tsagris, Abdulaziz Alenazi, Nikolaos Pandis   +2 more
exaly  

A non-parametric hypothesis test via the Bootstrap resampling

2000
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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