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Found 461 dataset(s) matching "Bayesian modeling".
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Python module "optbayesexpt" uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given a parametric model -...
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Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
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Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
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Map of nesting habitat selection scores predicted from a resource selection function (RSF) developed from sage-grouse nest locations. Nest site selection was modeled using a generalized linear...
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The Excel file contains the model input-out data sets that where used to evaluate the two-layer soil moisture and flux dynamics model. The model is original and was developed by Dr. Hantush by...
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The estimation of remaining useful life (RUL) of a faulty component is at the center of system prognostics and health management. It gives operators a potent tool in decision making by quantifying...
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<p dir="ltr">These data come from a roughly 4-year study on the growth response of a highly invasive woody plant to the damage induced by its biological control agent (an insect) and to soil...
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<p dir="ltr">This dataset includes all the raw data and all the R statistical software code that we used to analyze the data and produce all the outputs that are in the figures, tables, and text...
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These data were compiled to explore the foraging ecology of Rainbow Trout (Oncorhynchus mykiss) in the Colorado River, Grand Canyon, Arizona. These data represent samples characterizing the...
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This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density estimate. We show...
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We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density estimate. We show how to...
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These data contain the supplementary results corresponding with the journal article: Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population...
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We developed a model for analyzing multi-year demographic data for long-lived animals and used data from a population of Agassiz’s desert tortoise (Gopherus agassizii) at the Desert Tortoise...
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These data contain supplemental results and model code from the North American Bat Monitoring Program's (NABat) integrated species distribution model (iSDM) for the tricolored bat (Perimyotis...
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<p>This dataset contains all the data and code needed to reproduce the analyses in the manuscript:</p> <p>Penn, H. J., & Read, Q. D. (2023). Stem borer herbivory dependent on interactions of...
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<h2>Summary</h2><p dir="ltr">This dataset includes all data and code required to reproduce the analyses presented in the manuscript <a href="https://doi.org/10.1094/PHYTOFR-12-24-0131-R"...
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Early Model-based Provisional Estimates of Drug Overdose, Suicide, and Transportation-related Deaths
This dataset provides model-based provisional estimates of the weekly numbers of drug overdose, suicide, and transportation-related deaths using “nowcasting” methods to account for the normal lag...
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In the literature, impulsive signals are mostly modeled by symmetric alpha-stable processes. To represent their temporal dependencies, usually autoregressive models with time-invariant...
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Ranked index of model-projected nest site selection integrated with nesting productivity (i.e., nest survival), demonstrating the spatial distribution of adaptive vs. maladaptive habitat selection...
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Ranked habitat classes for sage-grouse brood-rearing productivity at each 90 m pixel. Habitat classes represent areas where high brood selection and high brood survival intersected, whereas the...
