Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data—where the unit of observation is a curve or set of curves ...

Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

Missing data is almost always present in real datasets, and introduces several statistical issues. One fundamental issue is that, in the absence of strong uncheckable assumptions, effects of interest ...

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

Objective To determine how distinct combinations of resistance training prescription (RTx) variables (load, sets and frequency) affect muscle strength and hypertrophy. Data sources MEDLINE, Embase, ...

GAC Honda Applies for Patent on Vehicle Fault Diagnosis Based on Bayesian Networks, Enhancing Diagnostic Intuitiveness and Interpretability. GAC Honda's Innovative Technology Lead ...

Symmetries in nature make things beautiful; symmetries in data make data handling efficient. However, the complexity of identifying such patterns in data has always bedeviled researchers. Scientists ...