LEADER 00000cam a2200697 i 4500 
003    OCoLC 
005    20240129213017.0 
006    m     o  d         
007    cr cnu---unuuu 
008    200815t20212021nju     ob    001 0 eng   
010      2020026631 
019    1266651507 
020    9781119417408|qelectronic book 
020    1119417406|qelectronic book 
020    9781119417392|qelectronic book 
020    1119417392|qelectronic book 
020    9781119417415|qelectronic book 
020    1119417414|qelectronic book 
020    |qhardcover 
029 1  AU@|b000067928953 
029 1  AU@|b000070668077 
035    (OCoLC)1193558110|z(OCoLC)1266651507 
037    9781119417385|bO'Reilly Media 
040    DLC|beng|erda|cDLC|dOCLCO|dOCLCF|dDG1|dOCLCO|dUKAHL|dYDX
       |dORMDA|dOCLCO|dOCLCQ|dOCLCO|dOCLCL 
042    pcc 
049    INap 
082 00 005.7 
082 00 005.7|223 
099    eBook O'Reilly for Public Libraries 
100 1  Peña, Daniel,|d1948-|eauthor. 
245 10 Statistical learning for big dependent data /|cDaniel Peña
       , Ruey S. Tsay.|h[O'Reilly electronic resource] 
250    First edition. 
264  1 Hoboken, NJ :|bJohn Wiley & Sons, Inc.,|c2021. 
264  4 |c©2021 
300    1 online resource. 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
490 1  Wiley series in probability and statistics 
504    Includes bibliographical references and index. 
505 0  Introduction to big dependent data -- Linear univariate 
       time series -- Analysis of multivariate time series -- 
       Handling heterogeneity in many time series -- Clustering 
       and classification of time series -- Dynamic factor models
       -- Forecasting with big dependent data -- Machine learning
       of big dependent data -- Spatio-temporal dependent data. 
520    "This book presents methods useful for analyzing and 
       understanding large data sets that are dynamically 
       dependent. The book will begin with examples of 
       multivariate dependent data and tools for presenting 
       descriptive statistics of such data. It then introduces 
       some useful statistical methods for univariate time series
       analysis emphasizing on statistical procedures for 
       modeling and forecasting. Both linear and nonlinear models
       are discussed. Special attention is given to analysis of 
       high-frequency dependent data. The second part of the book
       considers joint dependency, both contemporaneous and 
       dynamical dependence, among multiple series of dependent 
       data. Special attention will be given to graphical methods
       for large data, to handling heterogeneity in time series 
       (such as outliers, missing values, and changes in the 
       covariance matrices), and to time-varying parameters for 
       multivariate time series. The third part of the book is 
       devoted to analysis of high-dimensional dependent data. 
       The focus is on topics that are useful when the number of 
       time series is large. The selected topics include 
       clustering time series, high-dimensional linear regression
       for dependent data and its applications, and reducing the 
       dimension with dynamic principal components and factor 
       models. Throughout the book, advantages and disadvantages 
       of the methods discussed are given and real examples are 
       used in demonstration. The book will be of interest to 
       graduate students, researchers, and practitioners in 
       business, economics, engineering, and science who are 
       interested in statistical methods for analyzing big 
       dependent data and forecasting"--|cProvided by publisher. 
588    Description based on online resource; title from digital 
       title page (viewed on July 08, 2021). 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Big data|xMathematics. 
650  0 Time-series analysis. 
650  0 Data mining|xStatistical methods. 
650  0 Forecasting|xStatistical methods. 
650  6 Données volumineuses|xMathématiques. 
650  6 Série chronologique. 
650  6 Prévision|xMéthodes statistiques. 
650  7 Data mining|xStatistical methods|2fast 
650  7 Forecasting|xStatistical methods|2fast 
650  7 Time-series analysis|2fast 
700 1  Tsay, Ruey S.,|d1951-|eauthor. 
776 08 |iPrint version:|aPeña, Daniel, 1948-|tStatistical 
       learning for big dependent data|bFirst edition.|dHoboken, 
       NJ : Wiley, 2021.|z9781119417385|w(DLC)  2020026630 
830  0 Wiley series in probability and statistics. 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9781119417385/?ar
       |zAvailable on O'Reilly for Public Libraries 
938    Askews and Holts Library Services|bASKH|nAH37731881 
994    92|bJFN