Results 11 to 20 of about 814 (166)
The Information Geometry of Sparse Goodness-of-Fit Testing
Entropy, 2016 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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Testing Goodness-of-Fit with the Kernel Density Estimator: GoFKernel
Journal of Statistical Software, 2015 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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Frontiers in Psychology, 2021 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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sphstat: A Python package for inferential statistics on vectorial data on the unit sphere
SoftwareX, 2023 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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Testing Multivariate Normality Based on F-Representative Points
Mathematics, 2022 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
Forecasting, 2021 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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Efficient algorithm for testing goodness-of-fit for classification of high dimensional data
Lietuvos Matematikos Rinkinys, 2009 Let us have a sample satisfying d-dimensional Gaussian mixture model (d is supposed to be large). The problem of classification of the sample is considered. Because of large dimension it is natural to project the sample to k-dimensional (k = 1, 2, . . .)
Gintautas Jakimauskas
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vsgoftest: An R Package for Goodness-of-Fit Testing Based on Kullback-Leibler Divergence
Journal of Statistical Software, 2020 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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Goodness of Fit Approach for Testing Exponential Better than Used in Convex for Life Distributions [PDF]
The Egyptian Statistical Journal, 2004 Test statistic is derived for testing exponentiality against exponential better (worse) than used in convex EBUC (EWUC). Selected critical values are tabulated for sample size n=5(1)25(5) 50.
M. Hendi, N. AL-Ghufily
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International Journal of Energy and Environmental Engineering, 2018 Wind energy has been explored as a viable alternative to fossil fuels in many small island developing states such as those in the Caribbean for a long time. Central to evaluating the feasibility of any wind energy project is choosing the most appropriate
Isa Dookie +3 more
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