Overview:Biostatistics courses now effectively combine theory with real-world healthcare datasets and analytical ...
In the wake of the replication crisis, statistical power has become one of the central issues in debates about the quality of research. The widespread use of tests with low power is seen as a key ...
Abstract: The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a ...
Copyright: © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Frequentist and Bayesian ...
Simulation is an indispensable tool in both engineering and the sciences. In simulation-based modeling, a parametric simulator is adopted as a mechanistic model of a physical system. The problem of ...
ABSTRACT: In the present work, we are interested in studying the joint distributions of pairs of the monthly maxima of the pollutants used by the environmental authorities in Mexico City to classify ...
Artificial intelligence (AI) techniques are constantly changing scientific research, but their potential to enhance simulation pipelines is not widely recognised. Conversely, Bayesian inference is a ...
Abstract: The debiased estimator is a crucial tool in statistical inference for high-dimensional model parameters. However, constructing such an estimator involves estimating the high-dimensional ...
Abstract: With the increasing availability of electronic health records (EHR) data, it is important to effectively integrate evidence from multiple data sources to enable reproducible scientific ...
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