RT info:eu-repo/semantics/bookPart
T1 Some advances in constrained inference for ordered circular parameters in oscillatory systems
A1 Rueda Sabater, María Cristina
A1 Fernández Temprano, Miguel Alejandro
A1 Barragán, Sandra
A1 Peddada, Shyamal
AB Constraints on parameters arise naturally in many applications. Statistical methods thathonor the underlying constraints tend to be more powerful and result in better interpretationof the underlying scientific data. In the context of Euclidean space data, there existsover five decades of statistical literature on constrained statistical inference and at least fourbooks on the subject (e.g. Robertson et al. 1988; Silvapulle and Sen 2005). However, it wasnot until recently that these methods have been used extensively in applied research. Forexample, constrained statistical inference is gaining considerable interest among appliedresearchers in a variety of fields, such as, for example, toxicology (Peddada et al. 2007),genomics (Hoenerhoff et al. 2013; Perdivara et al. 2011; Peddada et al. 2003), epidemiology(Cao et al. 2011; Peddada et al. 2005), clinical trials (Conaway et al. 2004), or cancertrials (Conde et al. 2012, 2013).
PB Wiley
YR 2015
FD 2015
LK http://uvadoc.uva.es/handle/10324/22917
UL http://uvadoc.uva.es/handle/10324/22917
LA eng
NO Dryden, Kent (coords). Geometry Driven Statistics. Wiley 2015, p. 97-114.
DS UVaDOC
RD 24-abr-2024