Results 21 to 30 of about 22,043,161 (356)
A bootstrap approach to evaluating the performance of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in selection of an asymmetric price relationship [PDF]
Journal of Agricultural Sciences (Belgrade), 2012 This study addresses the problem of model selection in asymmetric price transmission models by combining the use of bootstrap methods with information theoretic selection criteria.
Acquah Henry de-Graft
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Bootstrap Model Ensemble and Rank Loss for Engagement Intensity Regression [PDF]
International Conference on Multimodal Interaction, 2019 This paper presents our approach for the engagement intensity regression task of EmotiW 2019. The task is to predict the engagement intensity value of a student when he or she is watching an online MOOCs video in various conditions.
Kai Wang +5 more
semanticscholar +1 more source
PLoS ONE, 2023 Machine learning methods are widely used within the medical field. However, the reliability and efficacy of these models is difficult to assess, making it difficult for researchers to identify which machine-learning model to apply to their dataset.
Alexander A. Huang, Samuel Y. Huang
semanticscholar +1 more source
Smoothed estimator of the periodic hazard function [PDF]
Opuscula Mathematica, 2009 A smoothed estimator of the periodic hazard function is considered and its asymptotic probability distribution and bootstrap simultaneous confidence intervals are derived.
Anna Dudek
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Entropy, 2020 Information dynamics and computational mechanics provide a suite of measures for assessing the information- and computation-theoretic properties of complex systems in the absence of mechanistic models.
David Darmon
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A discrete model for bootstrap iteration [PDF]
Journal of Econometrics, 2015 The bootstrap can be validated by considering the sequence of P values obtained by bootstrap iteration, rather than asymptotically. If this sequence converges to a random variable with the uniform U(0,1) distribution, the bootstrap is valid. Here, the model is made discrete and finite, characterised by a three-dimensional array of probabilities.
Russell Davidson, Russell Davidson
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Comparison of cross-validation and bootstrap aggregating for building a seasonal streamflow forecast model [PDF]
Proceedings of the International Association of Hydrological Sciences, 2016 Based on a hindcast experiment for the period 1982–2013 in 66 sub-catchments of the Swiss Rhine, the present study compares two approaches of building a regression model for seasonal streamflow forecasting.
S. Schick +5 more
doaj +1 more source
Bootstrapping the Kronig-Penney model
Physical Review D, 2022 21 pages, 5 figures, typos corrected, version to appear in Physical Review ...
Matthew J. Blacker +2 more
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Stats, 2022 The bootstrap method is often used for variance estimation in sample surveys with a stratified multistage sampling design. It is typically implemented by producing a set of bootstrap weights that is made available to users and that accounts for the ...
Jean-François Beaumont, Nelson Émond
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Bootstrapping periodically autoregressive models [PDF]
ESAIM: Probability and Statistics, 2017 The main objective of this paper is to establish the residual and the wild bootstrap procedures for periodically autoregressive models. We use the least squares estimators of model’s parameters and generate their bootstrap equivalents. We prove that the bootstrap procedures for causal periodic autoregressive time series with finite fourth moments are ...
Ciołek, Gabriela, Potorski, Paweł
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