Lehigh researchers create new method that improves consistency between predicted and observed data. An international team of mathematicians led by Lehigh University statistician Taeho Kim has ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are ...

We introduce the spherically projected multivariate linear model for directional data. This model treats directional observations as projections onto the unit sphere of unobserved responses from a ...

Researchers in Sweden have developed a method to use LiDAR data to enable more precise tilt and azimuth modeling of solar PV and solar thermal capacity at a regional or substation level. The model ...