Advances: And Innovations In Statistics And Data...

: Handling incomplete functional observations.

: Addressing identifiability and estimation in models where variables are measured with error, such as Autoregressive ARCH models . 2. Innovations in Data Science Practice Advances and Innovations in Statistics and Data...

: Used for skewed, truncated, or contaminated data with outliers. : Handling incomplete functional observations

: Using geometric interpretations of distance for learning finite Gaussian mixtures, which provides robustness against model mis-specifications. Advances and Innovations in Statistics and Data...

: Techniques for data that represent parts of a whole (proportions or percentages), including specialized R packages .

: Innovating techniques for feature screening and variable selection in datasets where the number of variables far exceeds the number of observations.