000			02104nam a22004455i 4500
001			978-3-642-33657-7
003			DE-He213
005			20140220082855.0
007			cr nn 008mamaa
008			121026s2013 gw | s |||| 0|eng d
020			_a9783642336577 _9978-3-642-33657-7
024	7		_a10.1007/978-3-642-33657-7 _2doi
050		4	_aQA276-280
072		7	_aPBT _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.5 _223
100	1		_aSeber, George A.F. _eauthor.
245	1	0	_aAdaptive Sampling Designs _h[electronic resource] : _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 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Statistics, _x2191-544X
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.
650		0	_aStatistics.
650	1	4	_aStatistics.
650	2	4	_aStatistics, general.
650	2	4	_aStatistics for Life Sciences, Medicine, Health Sciences.
700	1		_aSalehi, Mohammad M. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642336560
830		0	_aSpringerBriefs in Statistics, _x2191-544X
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-33657-7
912			_aZDB-2-SMA
999			_c97404 _d97404