Imputation methods provide essential statistical tools for addressing missing data, thereby minimising bias and enhancing the reliability of parameter estimates. In statistical estimation, missing ...

In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...

Missing data can plague researchers in many scenarios, arising from incomplete surveys, experimental objects broken or destroyed, or data collection/computational errors. This short course will ...

There are data about practically everything these days, and they can be used to try to answer any number of questions. Do clinical trials really show a drug works? Can surveys really signal who’s ...

Digitalization has enabled businesses to record their operations in event logs where each activity in a business process is recorded as data with certain attributes such as a timestamp, event name etc ...

A new review published in Artificial Intelligence and Autonomous Systems（AIAS） highlights how artificial intelligence can tackle the pervasive problem of missing traffic data in intelligent ...