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作者:Erin M. Schliep , Alan E. Gelfand ...
来源:[J].Journal of Agricultural, Biological and Environmental Statistics(IF 1.235), 2018, Vol.23 (3), pp.334-357Springer
摘要:Abstract(#br)The distinction between an overlap in species daily activity patterns and proximate co-occurrence of species for a location and time due to behavioral attraction or avoidance is critical when addressing the question of species co-occurrence. We use data from a d...
作者:Erin M. Schliep , Jennifer A. Hoeting
来源:[J].Computational Statistics and Data Analysis(IF 1.304), 2015, Vol.90, pp.1-14Elsevier
摘要:Abstract(#br)Data augmentation and parameter expansion can lead to improved iterative sampling algorithms for Markov chain Monte Carlo (MCMC). Data augmentation allows for simpler and more feasible simulation from a posterior distribution. Parameter expansion accelerates converge...
作者:Erin M. Schliep , Alan E. Gelfand , James S. Clark
来源:[J].Journal of Agricultural, Biological, and Environmental Statistics(IF 1.235), 2015, Vol.20 (3), pp.323-342Springer
摘要:Abstract(#br)The velocity of climate change is defined as an instantaneous rate of change needed to maintain a constant climate. It is developed as the ratio of the temporal gradient of climate change over the spatial gradient of climate change. Ecologically, understanding t...
作者:Erin M. Schliep , Alan E. Gelfand ...
来源:[J].Environmental and Ecological Statistics(IF 0.868), 2016, Vol.23 (1), pp.23-41Springer
摘要:Abstract(#br)Predictions of above-ground biomass and the change in above-ground biomass require attachment of uncertainty due the range of reported predictions for forests. Because above-ground biomass is seldom measured, there have been no opportunities to obtain such uncertaint...
作者:Erin M. Schliep , Jennifer A. Hoeting
来源:[J].Journal of Agricultural, Biological, and Environmental Statistics(IF 1.235), 2013, Vol.18 (4), pp.492-513Springer
摘要:Abstract(#br)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 an effort to quant...
作者:Erin M. Schliep , Daniel Cooley ...
来源:[J].Extremes(IF 1.395), 2010, Vol.13 (2), pp.219-239Springer
摘要:Abstract(#br)We analyze output from six regional climate models (RCMs) via a spatial Bayesian hierarchical model. The primary advantage of this approach is that the statistical model naturally borrows strength across locations via a spatial model on the parameters of the generali...
作者:Tyler Wagner , Erin M. Schliep
来源:[J].Limnology and Oceanography(IF 3.405), 2018, Vol.63 (6), pp.2372-2383Wiley
摘要:Abstract(#br)Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape‐based regressions are also used to understand macroscale variability of lake nutrients, clarity, and pr...
作者:Erin M. Schliep , Christopher T. Filstrup
来源:[J].Limnology and Oceanography: Methods(IF 1.946), 2019, Vol.17 (12), pp.639-649Wiley
摘要:Abstract(#br)There are multiple protocols for determining total nitrogen (TN) in water, but most can be grouped into direct approaches (TN‐d) that convert N forms to nitrogen‐oxides (NOx) and combined approaches (TN‐c) that combine Kjeldahl N (organic N +NH...
作者:Erin M. Schliep , Robert N. Schaeffer ...
来源:[J].Ecology(IF 5.175), 2018, Vol.99 (5), pp.1018-1023Wiley
摘要:Abstract(#br)A species’ distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out...

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