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Estimating effective sample size for...

Smith, Rebecca.

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Estimating effective sample size for spatially correlated data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Estimating effective sample size for spatially correlated data./
Author:	Smith, Rebecca.
Description:	76 p.
Notes:	Source: Masters Abstracts International, Volume: 52-06.
Contained By:	Masters Abstracts International52-06(E).
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1554748
ISBN:	9781303859519

Estimating effective sample size for spatially correlated data.
Smith, Rebecca.

Estimating effective sample size for spatially correlated data. - 76 p.

Source: Masters Abstracts International, Volume: 52-06.

Thesis (M.S.)--University of Central Arkansas, 2014.

This item must not be sold to any third party vendors.

Correlated data has long been difficult or impossible to analyze with traditional statistical methods that typically require independent observations. One cannot simply use the sample size since the information content is clearly reduced due to the relationships between the observations. In this thesis, we propose a method to estimate the effective sample size (ESS) in common scale, in correlated data using a function called the measure of equivalent exchange (MEE), which has the eigenvalues of the correlation matrix of the data and a tuning parameter, tau, as its arguments. The efficacy of the proposed method will be demonstrated empirically via simulations of one-, two-, and three-dimensional spatially correlated fields, and by application. We conclude with possible future implementations in a more generalized covariance settings.

ISBN: 9781303859519Subjects--Topical Terms:

517247
Statistics.

Estimating effective sample size for spatially correlated data.
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020 $a 9781303859519
035 $a (MiAaPQ)AAI1554748
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040 $a MiAaPQ $c MiAaPQ
100 1 $a Smith, Rebecca. $3 3175435
245 1 0 $a Estimating effective sample size for spatially correlated data.
300 $a 76 p.
500 $a Source: Masters Abstracts International, Volume: 52-06.
500 $a Adviser: Patrick Carmack.
502 $a Thesis (M.S.)--University of Central Arkansas, 2014.
506 $a This item must not be sold to any third party vendors.
520 $a Correlated data has long been difficult or impossible to analyze with traditional statistical methods that typically require independent observations. One cannot simply use the sample size since the information content is clearly reduced due to the relationships between the observations. In this thesis, we propose a method to estimate the effective sample size (ESS) in common scale, in correlated data using a function called the measure of equivalent exchange (MEE), which has the eigenvalues of the correlation matrix of the data and a tuning parameter, tau, as its arguments. The efficacy of the proposed method will be demonstrated empirically via simulations of one-, two-, and three-dimensional spatially correlated fields, and by application. We conclude with possible future implementations in a more generalized covariance settings.
590 $a School code: 1605.
650 4 $a Statistics. $3 517247
650 4 $a Applied mathematics. $3 2122814
690 $a 0463
690 $a 0364
710 2 $a University of Central Arkansas. $b Mathematics. $3 3175436
773 0 $t Masters Abstracts International $g 52-06(E).
790 $a 1605
791 $a M.S.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1554748