MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03810cam a22004698i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
21709313 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250930144153.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
m |o d | |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr ||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
200815s2021 nju ob 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2020026631 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781119417385 |
| Qualifying information |
paperback |
| Terms of availability |
RM695.04 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Description conventions |
rda |
| Modifying agency |
UKM |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.7 |
| Edition information |
23 |
| 090 00 - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
QA76.9 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
.B45 3 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
PenÌa, Daniel, |
| Dates associated with a name |
1948- |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Statistical learning for big dependent data / |
| Statement of responsibility, etc. |
Daniel PenÌa, Ruey S. Tsay. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
First edition. |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
2101 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Hoboken, NJ : |
| Name of producer, publisher, distributor, manufacturer |
Wiley, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2021. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 490 0# - SERIES STATEMENT |
|---|
| Series statement |
Wiley series in probability and statistics |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
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 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
'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'-- |
| Assigning source |
Provided by publisher. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Description based on print version record and CIP data provided by publisher; resource not viewed. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data |
| General subdivision |
Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Time-series analysis. |
| 9 (RLIN) |
61130 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining |
| General subdivision |
Statistical methods. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Forecasting |
| General subdivision |
Statistical methods. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Tsay, Ruey S., |
| Dates associated with a name |
1951- |
| Relator term |
author. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| Main entry heading |
PenÌa, Daniel, 1948- |
| Title |
Statistical learning for big dependent data |
| Edition |
First edition. |
| Place, publisher, and date of publication |
Hoboken, NJ : Wiley, 2021. |
| International Standard Book Number |
9781119417385 |
| Record control number |
(DLC) 2020026630 |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) |
|---|
| a |
.b16964925 |
| b |
2022-12-22 |
| c |
2022-12-15 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
AM |
| Suppress in OPAC |
No |
| Call number prefix |
QA76.9 .B45 3 |
| 991 ## - LOCAL NOTE (NAMA FAKULTI/INSTITUT/PUSAT) |
|---|
| a |
Fakulti Teknologi Sains Maklumat |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Library |
PERPUSTAKAAN LINGKUNGAN KEDUA |
| Operator's initials, OID (RLIN) |
2022-12-15 |
| Cataloger's initials, CIN (RLIN) |
m |
| Material Type (Sierra) |
Printed Books |
| Language |
English |
| Country |
|
| -- |
0 |
| -- |
.b16964925 |
