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Non-parametric Hypothesis Testing and Confidence Intervals with Doubly Censored Data
Lifetime Data Analysis, 2003The non-parametric maximum likelihood estimator (NPMLE) of the distribution function with doubly censored data can be computed using the self-consistent algorithm (Tumbull, 1974). We extend the self-consistent algorithm to include a constraint on the NPMLE.
Chen, Kun, Zhou, Mai
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A Non Parametric Test of the Expected Utility Hypothesis
1990A nonparametric test of the expected utility hypothesis is developed. It is shown that the expected utility hypothesis holds if there exists a feasible solution to a system of linear inequalities. Furthermore, when a feasible solution exists boundaries on the coefficient of absolute risk aversion can be calculated explicitly.
Bar-Shira, Ziv, Bar-Shira, Ziv
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Non-parametric hypothesis tests
1989There are some hypothesis tests which do not require as many assumptions as the tests described in Chapter 10. However, these ‘non-parametric’ tests are less powerful than the corresponding ‘parametric’ tests, that is we are less likely to reject the null hypothesis and hence accept the alternative hypothesis, when the alternative hypothesis is correct.
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Non parametric hypothesis tests for comparing reliability functions
Communications in Statistics - Theory and Methods, 2016ABSTRACTIn reliability and related disciplines, comparing reliability functions of two (or more) aging processes is a crucial step in the process of determining reliability and understanding an aging process. The aim of this paper is to propose a non parametric statistical methodology to compare two populations based on their mean residual life ...
Chathuri L. Jayasinghe +1 more
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Using non-parametrics to inform parametric tests of Kuznets' hypothesis
Applied Economics Letters, 2001Simon Kuznets hypothesized that inequality in a country's distribution of income worsens in the early stages of its economic development and that the inequality improves as the country reaches higher stages of development (the ‘inverted U hypothesis’). Empirical support for the inverted U hypothesis has been mixed.
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The International Journal of Biostatistics, 2009
In multiple simultaneous hypothesis testing (MSHT), a significance thresholding function as a scalar statistic can be designed in an adaptive manner by sharing information among many tests performed simultaneously. By using such an adapted statistic, MSHT has greater detection power than tests using simple individual statistics.
Shigeyuki Oba, Shin Ishii
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In multiple simultaneous hypothesis testing (MSHT), a significance thresholding function as a scalar statistic can be designed in an adaptive manner by sharing information among many tests performed simultaneously. By using such an adapted statistic, MSHT has greater detection power than tests using simple individual statistics.
Shigeyuki Oba, Shin Ishii
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A parametric approach to kinship hypothesis testing using identity-by-descent parameters
Statistical Applications in Genetics and Molecular Biology, 2015AbstractThere is a large number of applications where family relationships need to be determined from DNA data. In forensic science, competing ideas are in general verbally formulated as the two hypotheses of a test. For the most common paternity case, the null hypothesis states that the alleged father is the true father against the alternative ...
García-Magariños, Manuel +4 more
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On basic life testing issues in medical research using non‐parametric hypothesis testing
Quality and Reliability Engineering International, 2023AbstractThe probability life distributions usually describe the time to event or survival time. Therefore, these life distributions play a crucial role in the analysis and projection of the maximum life expectancy using the Laplace transform technique for nonparametric hypothesis testing.
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A Parametric Copula-Based Framework for Hypothesis Testing Using Heterogeneous Data
IEEE Transactions on Signal Processing, 2011We 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 +2 more
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Non-parametric multivariate regression hypothesis testing
2012We 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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