Results 261 to 270 of about 40,800 (302)
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Parametric and nonparametric bootstrap methods for meta-analysis
Behavior Research Methods, 2005In a meta-analysis, the unknown parameters are often estimated using maximum likelihood, and inferences are based on asymptotic theory. It is assumed that, conditional on study characteristics included in the model, the between-study distribution and the sampling distributions of the effect sizes are normal.
Wim Van Den Noortgate +2 more
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A parametric bootstrap approach for the equality of coefficients of variation
Computational Statistics, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ali Akbar Jafari, Mohammad Reza Kazemi
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Non-parametric and unsupervised Bayesian classification with Bootstrap sampling
Image and Vision Computing, 2004Abstract In this paper, we propose a non-parametric and unsupervised Bayesian classification based on the principle of Bootstrap sampling (BS) which reduces the dependence effect of pixels in real images, and reduces the classification time. Given an original image, we randomly select a small representative set of pixels.
Mourad Zribi
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On Parametric Bootstrapping and Bayesian Prediction
Scandinavian Journal of Statistics, 2004Abstract. We investigate bootstrapping and Bayesian methods for prediction. The observations and the variable being predicted are distributed according to different distributions. Many important problems can be formulated in this setting. This type of prediction problem appears when we deal with a Poisson process.
Fushiki, Tadayoshi +2 more
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Bootstrapping Parametric Models of Mortality
Scandinavian Actuarial Journal, 2004We consider a general problem of modeling a mortality law of a population of failing units with some parametric function. In this setting we define a mortality table of crude rates as a statistical estimator with multinomial distribution and show its consistency as well as asymptotic normality.
Grzegorz A. Rempala +1 more
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Parametric bootstrapping with nuisance parameters
Statistics & Probability Letters, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Young, GA, Lee, SMS
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Non-parametric bootstrap recycling
Statistics and Computing, 2002The double bootstrap provides diagnostics for bootstrap calculations and, if need be, appropriate adjustments. The amount of computation involved is usually considerable, and recycling provides a less computer intensive alternative. Recycling consists of using repeatedly the same samples drawn from a recycling distribution G for estimation under each ...
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Copula model evaluation based on parametric bootstrap
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Aristidis K. Nikoloulopoulos +1 more
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Parametric Bootstrapping for Assessing Software Reliability Measures
2011 IEEE 17th Pacific Rim International Symposium on Dependable Computing, 2011The bootstrapping is a statistical technique to replicate the underlying data based on the resampling, and enables us to investigate the statistical properties. It is useful to estimate standard errors and confidence intervals for complex estimators of complex parameters of the probability distribution from a small number of data.
Toshio Kaneishi, Tadashi Dohi
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Assessing model mimicry using the parametric bootstrap
Journal of Mathematical Psychology, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wagenmakers, E.J. +3 more
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