Zobrazeno 1 - 10
of 198
pro vyhledávání: '"Hoeting, Jennifer A."'
Autor:
Hewitt, Joshua, Hoeting, Jennifer A.
We combine conditioning techniques with sparse grid quadrature rules to develop a computationally efficient method to approximate marginal, but not necessarily univariate, posterior quantities, yielding approximate Bayesian inference via Sparse grid
Externí odkaz:
http://arxiv.org/abs/1904.07270
Uncertainty in return level estimates for rare events, like the intensity of large rainfall events, makes it difficult to develop strategies to mitigate related hazards, like flooding. Latent spatial extremes models reduce uncertainty by exploiting s
Externí odkaz:
http://arxiv.org/abs/1810.07318
Autor:
Gorsich, Erin E., Webb, Colleen T., Merton, Andrew A., Hoeting, Jennifer A., Miller, Ryan S., Farnsworth, Matthew L., Swafford, Seth R., DeLiberto, Thomas J., Pedersen, Kerri, Franklin, Alan B., McLean, Robert G., Wilson, Kenneth R., Doherty, Paul F.
Publikováno v:
Ecological Applications, 2021 Mar 01. 31(2), 1-12.
Externí odkaz:
https://www.jstor.org/stable/27029180
While most spatial data can be modeled with the assumption that distant points are uncorrelated, some problems require dependence at both far and short distances. We introduce a model to directly incorporate dependence in phenomena that influence a d
Externí odkaz:
http://arxiv.org/abs/1612.06303
An important aspect of modeling spatially-referenced data is appropriately specifying the covariance function of the random field. A practitioner working with spatial data is presented a number of choices regarding the structure of the dependence bet
Externí odkaz:
http://arxiv.org/abs/1508.05973
Publikováno v:
In Journal of Statistical Planning and Inference January 2020 204:177-186
Publikováno v:
Environmetrics 2015, 26: 451-462
We consider the problem of selecting deterministic or stochastic models for a biological, ecological, or environmental dynamical process. In most cases, one prefers either deterministic or stochastic models as candidate models based on experience or
Externí odkaz:
http://arxiv.org/abs/1409.7715
Publikováno v:
Journal of Agricultural, Biological, and Environmental Statistics, 2019 Sep 01. 24(3), 426-443.
Externí odkaz:
https://www.jstor.org/stable/48702927
Publikováno v:
Computational Statistics & Data Analysis 84 (2015): 54-67
We consider the problem of estimating parameters of stochastic differential equations (SDEs) with discrete-time observations that are either completely or partially observed. The transition density between two observations is generally unknown. We pr
Externí odkaz:
http://arxiv.org/abs/1305.4390
Autor:
Schliep, Erin M., Hoeting, Jennifer A.
We propose a Bayesian model for mixed ordinal and continuous multivariate data to evaluate a latent spatial Gaussian process. Our proposed model can be used in many contexts where mixed continuous and discrete multivariate responses are observed in a
Externí odkaz:
http://arxiv.org/abs/1205.4163