000			02129nam a22003855i 4500
001			306549
003			MX-SnUAN
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008			150903s2013 gw | o |||| 0|eng d
020			_a9783642336577 _99783642336577
024	7		_a10.1007/9783642336577 _2doi
035			_avtls000360295
039		9	_a201509030603 _bVLOAD _c201405070257 _dVLOAD _y201402201429 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aSeber, George A.F. _eautor _9345850
245	1	0	_aAdaptive Sampling Designs : _bInference for Sparse and Clustered Populations / _cby George A.F. Seber, Mohammad M. Salehi.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_aIx, 70 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSpringerBriefs in Statistics, _x2191-544X
500			_aSpringer eBooks
505	0		_aBasic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation.
520			_aThis book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. The sample adapts to new information as it comes in. These methods are especially used for sparse and clustered populations. Written by two acknowledged experts in the field of adaptive sampling.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aSalehi, Mohammad M. _eautor _9345851
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783642336560
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-33657-7 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c306549 _d306549