The basis function approach for modeling autocorrelation in ecological data

Ecology - Tập 98 Số 3 - Trang 632-646 - 2017
Trevor J. Hefley1,2, Kristin Broms1, Brian M. Brost1, Frances E. Buderman1, Shannon L. Kay2, Henry R. Scharf2, John Tipton2, Perry J. Williams1,2, Mevin B. Hooten1,2,3
1Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado, 80523, USA
2Department of Statistics, Colorado State University, Fort Collins, Colorado 80523, USA
3U.S. Geological Survey Colorado Cooperative Fish and Wildlife Research Unit Fort Collins Colorado 80523 USA

Tóm tắt

AbstractAnalyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time‐series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.

Từ khóa


Tài liệu tham khảo

10.1201/b17115

10.1111/j.1467-9868.2008.00663.x

10.2307/1400521

10.1111/j.1600-0587.2009.05717.x

10.1007/978-0-387-45528-0

10.1016/j.tree.2008.10.008

10.1006/tpbi.1997.1331

10.1086/303199

10.2307/1940179

10.1111/2041-210X.12465

10.1890/14-0959.1

10.18637/jss.v014.i14

10.2307/2685361

10.1002/9781119115151

Cressie N., 2011, Statistics for spatio‐temporal data

10.1890/0012-9615(2006)76[323:EDDPNA]2.0.CO;2

10.1111/j.1600-0587.2012.07348.x

10.1146/annurev.ecolsys.110308.120159

10.1111/j.2041-210X.2012.00239.x

10.18637/jss.v063.i13

10.1002/9781118441862.ch7

10.1201/b16018

10.3354/meps341037

10.1890/0012-9658(2006)87[2603:SMIETF]2.0.CO;2

10.2307/2290838

10.1080/01621459.2016.1224714

10.1002/env.2331

10.1007/978-0-387-84858-7

10.1007/s40823-016-0008-7

10.1111/ele.12671

10.1007/s12080-013-0195-3

10.1007/s13253‐016‐0274‐1

10.1007/978-1-4471-0657-9_2

10.1515/9781400866557

Hodges J. S., 2013, Richly parameterized linear models: additive, time series, and spatial models using random effects

10.1198/tast.2010.10052

10.1890/08-0836.1

10.1111/1365-2656.12080

10.1890/14-0661.1

10.1080/01621459.2016.1246250

10.1023/A:1026001008598

10.1007/s10651-007-0016-1

10.1007/s10651-007-0040-1

10.1111/j.1467-9868.2012.01041.x

10.1002/wat2.1023

10.1007/978-1-4614-7138-7

10.1007/s13253-013-0143-0

10.1080/01621459.2015.1123632

Krainski E., 2016, The R‐INLA tutorial on SPDE models

10.1111/j.1472-4642.2006.00293.x

10.1080/01621459.1994.10476759

10.1201/9781420011340

10.2307/1939924

10.1007/BF00048036

10.2307/1941447

10.1111/j.1467-9868.2011.00777.x

Littell R. C., 2006, SAS for mixed models

Lorenz E. N.1956.Empirical orthogonal functions and statistical weather prediction.http://www.o3d.org/abracco/Atlantic/Lorenz1956.pdf

10.2307/2290839

10.1007/s10109-015-0213-7

Nason G., 2010, Wavelet methods in statistics with R

10.1002/9781118150658.ch13

10.18637/jss.v019.i02

10.1016/j.csda.2006.11.008

10.1214/10-STS326

10.1890/08-1668.1

10.1111/j.1541-0420.2006.00617.x

10.1214/ss/1177011926

10.1201/9780203492024

10.1017/CBO9780511755453

10.1201/9781420072884-c9

10.1007/978-1-4612-1494-6

Stroup W. W., 2012, Generalized linear mixed models: modern concepts, methods and applications

10.2307/143141

10.2193/0022-541X(2006)70[922:IADPON]2.0.CO;2

Wahba G., 1990, Comment on Cressie, American Statistician, 44, 255

10.1191/1471082x02st036oa

10.1890/0012-9658(2003)084[1382:HBMFPT]2.0.CO;2

10.1201/9781420072884-c8

10.1007/s11749-010-0209-z

10.1002/ecy.1643

10.1201/9781420010404

Wood S. N., 2016, Just Another Gibbs Additive Modeller: Interfacing JAGS and mgcv

10.1111/rssc.12068

10.1007/978-0-387-87458-6

Thông tin
Thông tin xuất bản

Ecology

Tập 98 Số 3

632-646

Thông tin tác giả