Global ETD Search
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Showing 1 to 4 of 4 for “"Posterior predictive distribution"”.
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Bayesian Active Structure Learning for Gaussian Process Probabilistic Programs
… we also formulate a second objective function, Predictive Information Gain (IG-P), that reduces uncertainty over the posterior predictive distribution. We empirically validate that active learning with our novel IG-K objective is able to more accurately infer the structure of synthetic datasets …
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Skew Normal Bayesian Asset Allocation
… allocation problem based on the skew-normal distribution assumption and extends the Bayesian asset allocation model obtained by assuming hidden truncation skew-normal returns. Hidden truncation model provides a flexible family of skewed alternatives to the classical k dimensional normal …
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A tripartite study on Bayesian estimation of photosynthetically active radiation, impacts of future climate, and adaptation strategies on crop production: a spatial model framework for the Eastern Kansas River Basin
… that daily PAR values generated from the posterior predictive distribution using the Gibbs sampler algorithm outperformed the PAR estimates from the traditional linear modeling approach. In addition, soybean yield estimates using PAR from the Bayesian framework as inputs, captured the …
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Spatial Infectious Disease Transmission Models: Variable Screening Methods and Logistic Formulation.
… and its performance is evaluated using a posterior predictive approach (Gardner, 2010). Moreover, we apply variable selection methods to the newly developed CL-ILMs to enhance model performance, improve interpretability, and minimize the risk of overfitting, ultimately leading to more …