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Estimating effective sample size for...

Smith, Rebecca.

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Estimating effective sample size for spatially correlated data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Estimating effective sample size for spatially correlated data./
作者:	Smith, Rebecca.
面頁冊數:	76 p.
附註:	Source: Masters Abstracts International, Volume: 52-06.
Contained By:	Masters Abstracts International52-06(E).
標題:	Statistics. -
電子資源:	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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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
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710 2 $a University of Central Arkansas. $b Mathematics. $3 3175436
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793 $a English
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