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Bayesian inference and the parametric bootstrap. [PDF]
Ann Appl Stat, 2012 The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families and are particularly simple starting from Jeffreys invariant prior. Because of the i.i.d.
Efron B.
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Validating Sequence Analysis Typologies Using Parametric Bootstrap. [PDF]
Sociol Methodol, 2021 In this article, the author proposes a methodology for the validation of sequence analysis typologies on the basis of parametric bootstraps following the framework proposed by Hennig and Lin (2015). The method works by comparing the cluster quality of an observed typology with the quality obtained by clustering similar but nonclustered data. The author
Studer M.
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Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications. [PDF]
PLoS ONE, 2015 In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of ...
Elias Chaibub Neto
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Energies, 2020 Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method.
Kun Mo Lee +3 more
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A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks [PDF]
HGG AdvancesSummary: Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables ...
Yi-Ting Tsai +7 more
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A parametric bootstrap control chart for Lindley Geometric percentiles. [PDF]
PLoS ONEControl charts are vital for quality control and process monitoring, helping businesses identify variations in production. Traditional control charts, like Shewhart charts, may not work well for skewed distributions, such as the Lindley geometric ...
Muthanna Ali Hussein Al-Lami +2 more
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A Parametric Bootstrap for Heavy Tailed Distributions [PDF]
SSRN Electronic Journal, 2011 It is known that Efron’s bootstrap of the mean of a distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap mean is not the same as the limiting distribution of the mean from the real sample. Moreover, the limiting bootstrap distribution is random
Adriana Cornea, Russell Davidson
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A Parametric Bootstrap for the Mean Measure of Divergence [PDF]
The International Journal of Biostatistics, 2020 Abstract For more than 50 years the Mean Measure of Divergence (MMD) has been one of the most prominent tools used in anthropology for the study of non-metric traits. However, one of the problems, in anthropology including palaeoanthropology (more often there), is the lack ...
F. Zertuche, A. Meza-Peñaloza
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International Journal of Analysis and Applications, 2023 The common parametric statistics used for testing two independent populations have often required the assumptions of normality and equal variances. Nonparametric tests have been used when assumptions of parametric tests cannot be achieved.
Wandee Wanishsakpong +2 more
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Permutation and Parametric Bootstrap Tests for Gene-Gene and Gene-Environment Interactions [PDF]
Annals of Human Genetics, 2011 Petra Bůzková +2 more
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