What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better ...
A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...
Introduction Asthma is a chronic respiratory disorder requiring ongoing medical management. This ecological study investigated the spatial and temporal patterns of notification rates for asthma from ...
This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...
Version of Record: This is the final version of the article. The authors present an interesting study using RL and Bayesian modelling to examine differences in learning rate adaptation in conditions ...
Bayesian analysis is being used with increasing frequency in critical care research and brings advantages and disadvantages compared to traditional Frequentist techniques. This study overviews this ...
1 Department of Agricultural Economics and Extension, North West University, Mafikeng, South Africa 2 Department of Agricultural Economics, University of the Free State, Bloemfontein, South Africa ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
The standardized precipitation index (SPI) measures meteorological drought relative to historical climatology by normalizing accumulated precipitation. Longer record lengths improve parameter ...
Copyright: © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Frequentist and Bayesian ...
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