Results 11 to 20 of about 347,353 (142)
The Information Geometry of Sparse Goodness-of-Fit Testing
This paper takes an information-geometric approach to the challenging issue of goodness-of-fit testing in the high dimensional, low sample size context where—potentially—boundary effects dominate. The main contributions of this paper are threefold: first,
Paul Marriott +3 more
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Statistical mediation analysis is used to investigate mechanisms through which a randomized intervention causally affects an outcome variable. Mediation analysis is often carried out in a pretest-posttest control group design because it is a common ...
Matthew J. Valente +2 more
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Quantum Chi-Squared and Goodness of Fit Testing [PDF]
The density matrix in quantum mechanics parameterizes the statistical properties of the system under observation, just like a classical probability distribution does for classical systems. The expectation value of observables cannot be measured directly,
Bahadur R. R. +10 more
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Testing Goodness-of-Fit with the Kernel Density Estimator: GoFKernel
To assess the goodness-of-fit of a sample to a continuous random distribution, the most popular approach has been based on measuring, using either L∞ - or L2 -norms, the distance between the null hypothesis cumulative distribution function and the ...
Jose M. Pavia
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sphstat: A Python package for inferential statistics on vectorial data on the unit sphere
Data that resides on the surface of a 2-sphere is common in various scientific fields, including physics, earth sciences, astronomy, and psychoacoustics.
Hüseyin Hacıhabiboğlu
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Asymptotically distribution-free goodness-of-fit testing for tail copulas [PDF]
Let $(X_1,Y_1),\ldots,(X_n,Y_n)$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution.
Can, Sami Umut +3 more
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Testing Multivariate Normality Based on F-Representative Points
The multivariate normal is a common assumption in many statistical models and methodologies for high-dimensional data analysis. The exploration of approaches to testing multivariate normality never stops.
Sirao Wang +3 more
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Assessing Goodness of Fit for Verifying Probabilistic Forecasts
The verification of probabilistic forecasts in hydro-climatology is integral to their development, use, and adoption. We propose here a means of utilizing goodness of fit measures for verifying the reliability of probabilistic forecasts.
Tae-Ho Kang +2 more
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Nonparametric checks for single-index models [PDF]
In this paper we study goodness-of-fit testing of single-index models. The large sample behavior of certain score-type test statistics is investigated. As a by-product, we obtain asymptotically distribution-free maximin tests for a large class of local ...
Stute, Winfried, Zhu, Li-Xing
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vsgoftest: An R Package for Goodness-of-Fit Testing Based on Kullback-Leibler Divergence
The R package vsgoftest performs goodness-of-fit (GOF) tests, based on Shannon entropy and Kullback-Leibler divergence, developed by Vasicek (1976) and Song (2002), of various classical families of distributions. The so-called Vasicek-Song (VS) tests are
Justine Lequesne, Philippe Regnault
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