000 02438nam a2200397 i 4500
001 CR9781139020893
003 UkCbUP
005 20240913180416.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 110217s2014||||enk o ||1 0|eng|d
020 _a9781139020893 (ebook)
020 _z9780521864015 (hardback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQA278.8
_b.G76 2014
082 0 0 _a519.5/4
_223
100 1 _aGroeneboom, P.,
_eauthor.
245 1 0 _aNonparametric estimation under shape constraints :
_bestimators, algorithms, and asymptotics /
_cPiet Groeneboom, Delft University of Technology, Geurt Jongbloed, Delft University of Technology.
264 1 _aCambridge :
_bCambridge University Press,
_c2014.
300 _a1 online resource (xi, 416 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aCambridge series on statistical and probabilistic mathematics ;
_v38
500 _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520 _aThis book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.
650 0 _aNonparametric statistics.
650 0 _aMultivariate analysis.
650 0 _aMathematical statistics.
650 0 _aEstimation theory.
700 1 _aJongbloed, Geurt,
_d1968-
_eauthor.
776 0 8 _iPrint version:
_z9780521864015
830 0 _aCambridge series on statistical and probabilistic mathematics ;
_v38.
856 4 0 _uhttps://doi.org/10.1017/CBO9781139020893
942 _2ddc
_cEB
999 _c9595
_d9595