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020 _a9780387245553
_9978-0-387-24555-3
024 7 _a10.1007/b105993
_2doi
035 _avtls000330075
039 9 _a201509030233
_bVLOAD
_c201405070457
_dVLOAD
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050 4 _aQA273.A1-274.9
100 1 _aDuchesne, Pierre.
_eeditor.
_9302440
245 1 0 _aStatistical Modeling and Analysis for Complex Data Problems /
_cedited by Pierre Duchesne, Bruno RÉMillard.
264 1 _aBoston, MA :
_bSpringer US,
_c2005.
300 _aXIV, 323 páginas,
_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 _aDependence Properties of Meta-Elliptical Distributions -- The Statistical Significance of Palm Beach County -- Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods -- Conditions for the Validity of F-Ratio Tests for Treatment and Carryover Effects in Crossover Designs -- Bias in Estimating the Variance of K-Fold Cross-Validation -- Effective Construction of Modified Histograms in Higher Dimensions -- On Robust Diagnostics at Individual Lags Using RA-ARX Estimators -- Bootstrap Confidence Intervals for Periodic Preventive Replacement Policies -- Statistics for Comparison of Two Independent cDNA Filter Microarrays -- Large Deviations for Interacting Processes in the Strong Topology -- Asymptotic Distribution of a Simple Linear Estimator for Varma Models in Echelon Form -- Recent Results for Linear Time Series Models with Non Independent Innovations -- Filtering of Images for Detecting Multiple Targets Trajectories -- Optimal Detection of Periodicities in Vector Autoregressive Models -- The Wilcoxon Signed-Rank Test for Cluster Correlated Data.
520 _aSTATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors—largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes—present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets. The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aRÉMillard, Bruno.
_eeditor.
_9302441
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387245546
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b105993
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c278667
_d278667