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121026s2013 gw | s |||| 0|eng d |
| 020 |
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|a 9783642336577
|9 978-3-642-33657-7
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| 024 |
7 |
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|a 10.1007/978-3-642-33657-7
|2 doi
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| 050 |
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4 |
|a QA276-280
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| 072 |
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7 |
|a PBT
|2 bicssc
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| 072 |
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|a MAT029000
|2 bisacsh
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0 |
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|a 519.5
|2 23
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| 100 |
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|a Seber, George A.F.
|e author.
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| 245 |
1 |
0 |
|a Adaptive Sampling Designs
|b Inference for Sparse and Clustered Populations /
|c by George A.F. Seber, Mohammad M. Salehi.
|h [electronic resource] :
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| 264 |
# |
1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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| 300 |
# |
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|a IX, 70 p.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a SpringerBriefs in Statistics,
|x 2191-544X
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| 505 |
0 |
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|a Basic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation.
|
| 520 |
# |
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|a This 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 |
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0 |
|a Statistics.
|
| 650 |
1 |
4 |
|a Statistics.
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| 650 |
2 |
4 |
|a Statistics, general.
|
| 650 |
2 |
4 |
|a Statistics for Life Sciences, Medicine, Health Sciences.
|
| 700 |
1 |
# |
|a Salehi, Mohammad M.
|e author.
|
| 710 |
2 |
# |
|a SpringerLink (Online service)
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| 773 |
0 |
# |
|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783642336560
|
| 830 |
# |
0 |
|a SpringerBriefs in Statistics,
|x 2191-544X
|
| 856 |
4 |
0 |
|z View fulltext via EzAccess
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-33657-7
|
| 912 |
# |
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|a ZDB-2-SMA
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| 950 |
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|a Mathematics and Statistics (Springer-11649)
|