Advances And Innovations In Statistics And Data... -
: Advancing efficient design for regularized linear models, ensuring that data collection is optimized for specific analytical goals. 3. Critical Applications
: Innovating techniques for feature screening and variable selection in datasets where the number of variables far exceeds the number of observations. Advances and Innovations in Statistics and Data...
: Handling incomplete functional observations. : Advancing efficient design for regularized linear models,
Recent innovations are primarily driven by real-world challenges in health and environmental sciences. Advances and Innovations in Statistics and Data Science including specialized R packages .
: Techniques for data that represent parts of a whole (proportions or percentages), including specialized R packages .
