Non-parametric bootstrap tests for parametric distribution families

2011 ◽  
Vol 77 (3-4) ◽  
pp. 703-723
Author(s):  
Gábor Szűcs
2014 ◽  
Vol 45 (1) ◽  
pp. 322-338 ◽  
Author(s):  
Liwen Xu ◽  
Kaiyi Qu ◽  
Mixia Wu ◽  
Bo Mei ◽  
Ranran Chen

2018 ◽  
Vol 48 (3) ◽  
pp. 199-204 ◽  
Author(s):  
R. LI ◽  
J. ZHOU ◽  
L. WANG

In this paper, the non-parametric bootstrap and non-parametric Bayesian bootstrap methods are applied for parameter estimation in the binary logistic regression model. A real data study and a simulation study are conducted to compare the Nonparametric bootstrap, Non-parametric Bayesian bootstrap and the maximum likelihood methods. Study results shows that three methods are all effective ways for parameter estimation in the binary logistic regression model. In small sample case, the non-parametric Bayesian bootstrap method performs relatively better than the non-parametric bootstrap and the maximum likelihood method for parameter estimation in the binary logistic regression model.


2007 ◽  
Vol 28 (16) ◽  
pp. 2273-2283 ◽  
Author(s):  
Mireya Diaz ◽  
J. Sunil Rao

2010 ◽  
Vol 75 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Petra Bůžková ◽  
Thomas Lumley ◽  
Kenneth Rice

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