Effective Sample Size for Line Transect Sampling Models with an Application to Marine Macroalgae

Content Provider	Semantic Scholar
Author	Acosta, Jonathan Osorio, Felipe Vallejos, R.
Copyright Year	2016
Abstract	This paper provides a framework for estimating the effective sample size in a spatial regression model context when the data have been sampled using a line transect scheme and there is an evident serial correlation due to the chronological order in which the observations were collected. We propose a linear regression model with a partially linear covariance structure to address the computation of the effective sample size when spatial and serial correlations are present. A recursive algorithm is described to separately estimate the linear and nonlinear parameters involved in the covariance structure. The kriging equations are also presented to explore the kriging variance between our proposal and a typical spatial regression model. An application in the context of marine macroalgae, which motivated the present work, is also presented.
Starting Page	407
Ending Page	425
Page Count	19
File Format	PDF HTM / HTML
DOI	10.1007/s13253-016-0252-7
Volume Number	21
Alternate Webpage(s)	http://fosorios.mat.utfsm.cl/files/preprint/16_JABES_ESS.pdf
Alternate Webpage(s)	https://doi.org/10.1007/s13253-016-0252-7
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article