000 03849nam a22005415i 4500
001 978-3-319-45575-4
003 DE-He213
005 20181204134229.0
007 cr nn 008mamaa
008 161110s2016 gw | s |||| 0|eng d
020 _a9783319455754
_9978-3-319-45575-4
024 7 _a10.1007/978-3-319-45575-4
_2doi
040 _aISI Library, Kolkata
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
072 7 _aPBWL
_2thema
082 0 4 _a519.2
_223
100 1 _aSamorodnitsky, Gennady.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aStochastic Processes and Long Range Dependence
_h[electronic resource] /
_cby Gennady Samorodnitsky.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXI, 415 p. 5 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
505 0 _aPreface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.
520 _aThis monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory). The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author’s own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been published in a single self-contained volume, and can be used for a one- or two-semester graduate topics course. It is complete with helpful exercises and an appendix which describes a number of notions and results belonging to the topics used frequently throughout the book, such as topological groups and an overview of the Karamata theorems on regularly varying functions.
650 0 _aDistribution (Probability theory.
650 0 _aMathematics.
650 0 _aDifferentiable dynamical systems.
650 1 4 _aProbability Theory and Stochastic Processes.
_0http://scigraph.springernature.com/things/product-market-codes/M27004
650 2 4 _aMeasure and Integration.
_0http://scigraph.springernature.com/things/product-market-codes/M12120
650 2 4 _aDynamical Systems and Ergodic Theory.
_0http://scigraph.springernature.com/things/product-market-codes/M1204X
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319455747
776 0 8 _iPrinted edition:
_z9783319455761
776 0 8 _iPrinted edition:
_z9783319833217
830 0 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598
856 4 0 _uhttps://doi.org/10.1007/978-3-319-45575-4
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c426543
_d426543