Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

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 ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

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 ...

ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...