000			03121nam a22003975i 4500
001			307238
003			MX-SnUAN
005			20160429160119.0
007			cr nn 008mamaa
008			150903s2013 gw | o |||| 0|eng d
020			_a9783642355127 _99783642355127
024	7		_a10.1007/9783642355127 _2doi
035			_avtls000360764
039		9	_a201509030629 _bVLOAD _c201405070304 _dVLOAD _y201402201439 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aBeran, Jan. _eautor _9346777
245	1	0	_aLong-Memory Processes : _bProbabilistic Properties and Statistical Methods / _cby Jan Beran, Yuanhua Feng, Sucharita Ghosh, Rafal Kulik.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_axvii, 884 páginas 89 ilustraciones, 60 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		_aDefinition of Long Memory -- Origins and Generation of Long Memory -- Mathematical Concepts -- Limit Theorems -- Statistical Inference for Stationary Processes -- Statistical Inference for Nonlinear Processes -- Statistical Inference for Nonstationary Processes -- Forecasting -- Spatial and Space-Time Processes -- Resampling -- Function Spaces -- Regularly Varying Functions -- Vague Convergence -- Some Useful Integrals -- Notation and Abbreviations.
520			_aLong-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aFeng, Yuanhua. _eautor _9346778
700	1		_aGhosh, Sucharita. _eautor _9309557
700	1		_aKulik, Rafal. _eautor _9346779
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783642355110
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-35512-7 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c307238 _d307238