Comments on: Augmenting the bootstrap to analyze high dimensional genomic data
págs. 1-2
Augmenting the bootstrap to analyze high dimensional genomic data
Svitlana Tyekucheva, Francesca Chiaromonte
págs. 2-18
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data I
Bing Li
págs. 19-21
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data II
Lexin Li
págs. 22-24
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data III
Korbinian Strimmer
págs. 25-27
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data IV
Juliane Schäfer
págs. 28-30
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data V
Anne-Laure Boulesteix, Athanassios Kondylis, Nicole Krämer
págs. 31-35
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data VI
Sündüz Keleş, Hyonho Chun
págs. 36-39
Comments on: Augmenting the bootstrap to analyze high dimensional genomic data VII
Geoffrey J. McLachlan, K. Wang, S. K. Ng
págs. 43-46
Rejoinder on: Augmenting the bootstrap to analyze high dimensional genomic data VIII
Svitlana Tyekucheva, Francesca Chiaromonte
págs. 47-55
Optimal allocation of bioassays in the case of parametrized covariance functions: an application to Lung’s retention of radioactive particles
M. Stehlik, Juan Manuel Rodríguez Díaz , Werner G. Müller, Jesús López Fidalgo
págs. 56-68
págs. 69-82
Decision theory classification of high-dimensional vectors based on small samples
David Bradshaw, Marianna Pensky
págs. 83-100
págs. 101-119
MANOVA for large hypothesis degrees of freedom under non-normality
Arjun K. Gupta, Solomon W. Harrar, Yasunori Fujikoshi
págs. 120-137
Optimal bandwidth selection for multivariate kernel deconvolution density estimation
Élie Youndjé, Martin T. Wells
págs. 138-162
págs. 163-178
págs. 179-196
págs. 197-210
© 2008-2024 Fundación Dialnet · Todos los derechos reservados