Adaptive Sampling Designs Inference for Sparse and Clustered Populations /

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 spar...

Full description

Main Authors: Seber, George A.F. (Author, http://id.loc.gov/vocabulary/relators/aut), Salehi, Mohammad M. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:SpringerBriefs in Statistics,
Subjects:
Online Access:https://doi.org/10.1007/978-3-642-33657-7
LEADER 02510nam a22004815i 4500
001 978-3-642-33657-7
003 DE-He213
005 20210706073008.0
007 cr nn 008mamaa
008 121026s2013 gw | s |||| 0|eng d
020 |a 9783642336577  |9 978-3-642-33657-7 
024 7 |a 10.1007/978-3-642-33657-7  |2 doi 
050 4 |a QA276-280 
072 7 |a PBT  |2 bicssc 
072 7 |a MAT029000  |2 bisacsh 
072 7 |a PBT  |2 thema 
082 0 4 |a 519.5  |2 23 
100 1 |a Seber, George A.F.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Adaptive Sampling Designs  |h [electronic resource] :  |b Inference for Sparse and Clustered Populations /  |c by George A.F. Seber, Mohammad M. Salehi. 
250 |a 1st ed. 2013. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a IX, 70 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a SpringerBriefs in Statistics,  |x 2191-544X 
505 0 |a Basic Ideas -- Adaptive Cluster Sampling -- Rao-Blackwell Modi -- Primary and Secondary Units -- Inverse Sampling Methods -- Adaptive Allocation. 
520 |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 0 |a Statistics . 
650 1 4 |a Statistics, general.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/S0000X 
650 2 4 |a Statistics for Life Sciences, Medicine, Health Sciences.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/S17030 
700 1 |a Salehi, Mohammad M.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783642336584 
776 0 8 |i Printed edition:  |z 9783642336560 
830 0 |a SpringerBriefs in Statistics,  |x 2191-544X 
856 4 0 |u https://doi.org/10.1007/978-3-642-33657-7 
912 |a ZDB-2-SMA 
912 |a ZDB-2-SXMS 
950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713)