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Investigation on the Improvement of Prediction by Bootstrap Model Averaging

Methods of Information in Medicine, 2006
N. Holländer, N. Augustin, W. Sauerbrei
semanticscholar   +1 more source

An overview of real‐world data sources for oncology and considerations for research

Ca-A Cancer Journal for Clinicians, 2022
Lynne Penberthy   +2 more
exaly  

Bootstrapping Latent Class Models

2005
This paper deals with improved measures of statistical accuracy for parameter estimates of latent class models. It introduces more precise confidence intervals for the parameters of this model, based on parametric and nonparametric bootstrap. Moreover, the label-switching problem is discussed and a solution to handle it introduced.
openaire   +1 more source

Bootstrapping Garch(1,1) Models

1998
In this paper we propose a bootstrap method for quasi-maximum likelihood (QML) estimators in GARCH(1,1) models. The wild bootstrap is used to bootstrap GARCH(1,1) processes and construct bootstrap QML estimators. It is shown that this bootstrap procedure “works” in the sense that it is consistent.
openaire   +1 more source

Bootstrapping in Multilevel Models

2015
We note, however, that even as the number of bootstrap replications tends to infinity, the estimate of the population density function that is used to generate the bootstrap samples is the empirical “plug in” one derived from the actual sampled observations by placing mass points (e.g., equal probabilities) at each one.
openaire   +1 more source

The biofilm life cycle: expanding the conceptual model of biofilm formation

Nature Reviews Microbiology, 2022
Karin Sauer   +2 more
exaly  

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