Goodness-of-fit testing for meta-analysis of rare binary events [PDF]
Scientific Reports, 2023 Random-effects (RE) meta-analysis is a crucial approach for combining results from multiple independent studies that exhibit heterogeneity. Recently, two frequentist goodness-of-fit (GOF) tests were proposed to assess the fit of RE model.
Ming Zhang +3 more
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Nonparametric goodness‐of‐fit testing for parametric covariate models in pharmacometric analyses [PDF]
CPT: Pharmacometrics & Systems Pharmacology, 2021 The characterization of covariate effects on model parameters is a crucial step during pharmacokinetic/pharmacodynamic analyses. Although covariate selection criteria have been studied extensively, the choice of the functional relationship between ...
Niklas Hartung +3 more
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vsgoftest: An R Package for Goodness-of-Fit Testing Based on Kullback-Leibler Divergence [PDF]
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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Remember the Curse of Dimensionality: The Case of Goodness-of-Fit Testing in Arbitrary Dimension [PDF]
, 2018 Despite a substantial literature on nonparametric two-sample goodness-of-fit testing in arbitrary dimensions spanning decades, there is no mention there of any curse of dimensionality. Only more recently Ramdas et al.
Arias-Castro, Ery +2 more
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Goodness-of-fit testing based on a weighted bootstrap: A fast large-sample alternative to the parametric bootstrap [PDF]
, 2012 The process comparing the empirical cumulative distribution function of the sample with a parametric estimate of the cumulative distribution function is known as the empirical process with estimated parameters and has been extensively employed in the ...
Kojadinovic, Ivan, Yan, Jun
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Goodness-of-fit testing and quadratic functional estimation from indirect observations [PDF]
, 2007 We consider the convolution model where i.i.d. random variables $X_i$ having unknown density $f$ are observed with additive i.i.d. noise, independent of the $X$'s. We assume that the density $f$ belongs to either a Sobolev class or a class of supersmooth
Butucea, Cristina
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Estimation of integrated volatility of volatility with applications to goodness-of-fit testing [PDF]
, 2015 In this paper, we are concerned with nonparametric inference on the volatility of volatility process in stochastic volatility models. We construct several estimators for its integrated version in a high-frequency setting, all based on increments of spot ...
Vetter, Mathias
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Improved kernel estimation of copulas: Weak convergence and goodness-of-fit testing [PDF]
, 2009 We reconsider the existing kernel estimators for a copula function, as proposed in Gijbels and Mielniczuk [Comm. Statist. Theory Methods 19 (1990) 445--464], Fermanian, Radulovi\v{c} and Wegkamp [Bernoulli 10 (2004) 847--860] and Chen and Huang [Canad. J.
Gijbels, Irène +2 more
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Limited-information goodness-of-fit testing of hierarchical item factor models. [PDF]
Br J Math Stat Psychol, 2013 Cai L, Hansen M.
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Adaptive goodness-of-fit testing from indirect observations [PDF]
, 2009 International audienceIn a convolution model, we observe random variables whose distribution is the convolution of some unknown density $f$ and some known noise density $g$. We assume that $g$ is polynomially smooth.
Butucea, Cristina +2 more
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