Zobrazeno 1 - 10
of 2 021
pro vyhledávání: '"M. Ver"'
Autor:
Santos-Fernandez, Edgar, Hoef, Jay M. Ver, Peterson, Erin E., McGree, James, Villa, Cesar A., Leigh, Catherine, Turner, Ryan, Roberts, Cameron, Mengersen, Kerrie
The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are prone to technical anomalies that can undermine the trustworthiness o
Externí odkaz:
http://arxiv.org/abs/2409.07667
We consider four main goals when fitting spatial linear models: 1) estimating covariance parameters, 2) estimating fixed effects, 3) kriging (making point predictions), and 4) block-kriging (predicting the average value over a region). Each of these
Externí odkaz:
http://arxiv.org/abs/2305.07811
Autor:
Hoef, Jay M. Ver, Blagg, Eryn, Dumelle, Michael, Dixon, Philip M., Zimmerman, Dale L., Conn, Paul
Publikováno v:
Environmetrics, 2024, e2872
Using a hierarchical construction, we develop methods for a wide and flexible class of models by taking a fully parametric approach to generalized linear mixed models with complex covariance dependence. The Laplace approximation is used to marginally
Externí odkaz:
http://arxiv.org/abs/2305.02978
Autor:
Santos-Fernandez, Edgar, Hoef, Jay M. Ver, McGree, James M., Isaak, Daniel J., Mengersen, Kerrie, Peterson, Erin E.
Spatio-temporal models are widely used in many research areas from ecology to epidemiology. However, most covariance functions describe spatial relationships based on Euclidean distance only. In this paper, we introduce the R package SSNbayes for fit
Externí odkaz:
http://arxiv.org/abs/2202.07166
Autor:
Santos-Fernandez, Edgar, Hoef, Jay M. Ver, Peterson, Erin E., McGree, James, Isaak, Daniel, Mengersen, Kerrie
Spatio-temporal models are widely used in many research areas including ecology. The recent proliferation of the use of in-situ sensors in streams and rivers supports space-time water quality modelling and monitoring in near real-time. A new family o
Externí odkaz:
http://arxiv.org/abs/2103.03538
Publikováno v:
Spatial Staistics, Volume 43, 2021
We describe spatio-temporal random processes using linear mixed models. We show how many commonly used models can be viewed as special cases of this general framework and pay close attention to models with separable or product-sum covariances. The pr
Externí odkaz:
http://arxiv.org/abs/2005.00952
Autor:
Pearse, Alan R., McGree, James M., Som, Nicholas A., Leigh, Catherine, Hoef, Jay M. Ver, Maxwell, Paul, Peterson, Erin E.
Streams and rivers are biodiverse and provide valuable ecosystem services. Maintaining these ecosystems is an important task, so organisations often monitor the status and trends in stream condition and biodiversity using field sampling and, more rec
Externí odkaz:
http://arxiv.org/abs/1912.00540
Environmental data may be "large" due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates with nonlinear relationships, whereas spatial regression, when using
Externí odkaz:
http://arxiv.org/abs/1812.10236
We clarify relationships between conditional (CAR) and simultaneous (SAR) autoregressive models. We review the literature on this topic and find that it is mostly incomplete. Our main result is that a SAR model can be written as a unique CAR model, a
Externí odkaz:
http://arxiv.org/abs/1710.07000
Publikováno v:
Bulletin of the Ecological Society of America, 2020 Jul 01. 101(3), 1-5.
Externí odkaz:
https://www.jstor.org/stable/26920158
