0376411 20240103200824.720120511235959.9 000298264900002 10.1017/S2040174411000572 8 s. cav_un_epca*03764102040-174426 (2011)322-329 data depth contours growth curves nonparametric Bayes cav_un_auth*0280800 McKeague I. W. US cav_un_auth*0280801 López-Pintado S. ES cav_un_auth*0280802 Hallin M. BE cav_un_auth*0266474 Šiman Miroslav Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2011/SI/siman-0376411.pdf 1M06047 GA MŠk CZ cav_un_auth*0217941 CEZ:AV0Z10750506 This article proposes some new nonparametric approaches to analyzing sparse data on growth trajectories, with flexibility and ease of implementation being key features. The methods are illustrated using data on participants in the Collaborative Perinatal Project. 2013 BB http://hdl.handle.net/11104/0208817 PUBLICENVIRONMENTALOCCUPATIONALHEALTH 1.556 0.452 0.00047 0.572 90 42 0.571 29.589 51.582 Q3 Q3 2011 000298264900002 WOS cav_un_epca*0376410 Journal of Developmental Origins of Health and Disease 2040-1744 2040-1752 Roč. 2 č. 6 2011 322 329