000 04197nam a22003855i 4500
001 280929
003 MX-SnUAN
005 20160429154043.0
007 cr nn 008mamaa
008 150903s2012 xxu| o |||| 0|eng d
020 _a9780817648015
_99780817648015
024 7 _a10.1007/9780817648015
_2doi
035 _avtls000333647
039 9 _a201509030206
_bVLOAD
_c201404130506
_dVLOAD
_c201404092255
_dVLOAD
_y201402041116
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aChen, Jie.
_eautor
_9306205
245 1 0 _aParametric Statistical Change Point Analysis :
_bWith Applications to Genetics, Medicine, and Finance /
_cby Jie Chen, Arjun K. Gupta.
250 _aSecond Edition.
264 1 _aBoston :
_bBirkhäuser Boston,
_c2012.
300 _axiii, 273 páginas 24 ilustraciones, 23 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aPreface -- Preliminaries -- Introduction -- Univariate Normal Model -- Multivariate Normal Model -- Regression Model -- Gamma Model -- Exponential Model -- Change Point Model for the Hazard Function -- Discrete Models -- Other Models -- Bibliography -- Author Index -- Subject Index.
520 _aOverall, the book gives a clear and systematic presentation of models and methods. It will be an excellent source for theoretical and applied statisticians who are interested in research on change-point analysis and its applications to many areas.   —Mathematical Reviews (Review of the First Edition) Revised and expanded, Parametric Statistical Change Point Analysis, Second Edition is an in-depth study of the change point problem from a general point of view, and a deeper look at change point analysis of the most commonly used statistical models. For some time, change point problems have appeared throughout the sciences in such disciplines as economics, medicine, psychology, signal processing, and geology; more recently, they have also been found extensively in applications related to biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data. These areas of interest—new and old—have motivated substantial research on change point problems and led to a significant body of literature in the field. The present monograph stands as a valuable contribution to this literature. Key features and topics:  * Clear and systematic exposition with a great deal of introductory material included;  * Different models in each chapter, including gamma and exponential models, rarely examined thus far in the literature;  * Extensive examples to emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as the Bayesian and information criterion approaches;  * An up-to-date comprehensive bibliography and two indices. New to the Second Edition:  * New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control;  * Two new sections of applications of the underlying change point models in analyzing the array Comparative Genomic Hybridization (aCGH) data for DNA copy number changes;  * A new chapter on change points in the hazard function;  * A new chapter on other practical change point models, such as the epidemic change point model and a smooth-and-abrupt change point model. This monograph will be a highly useful resource for an impressively broad range of researchers in statistics, as well as a useful supplement for graduate courses in the field.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aGupta, Arjun K.
_eautor
_9306206
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780817648008
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-8176-4801-5
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c280929
_d280929