Evelina Maines, Riccardo Pertile, Vittoria Cauvin, Massimo Soffiati, Roberto Franceschi
Glucose metrics improvement in youths with type 1 diabetes using the Ambulatory Glucose Profile report: A real-world study
Diabetes research and clinical practice
even ubiquitous sensing data intelligent transportation systems mobile sensing vehicle trajectories traffic estimation still faced data missing problem due detector faults limited number probe vehicles mobile sensors data missing issue poses obstacle many explorations eg linkbased traffic status modeling although many studies focused tackling kind problem existing studies mainly focus situation data missing random ignore distinction links missing data practical scenario traffic speed data always missing random mnar distinction recovering missing data different links studied yet paper propose general linear model based probabilistic principal component analysis ppca solving mnar traffic speed data imputation furthermore propose metric ie pearson score pscore distinguishing links investigate model performs links different pscore values experimental results show new model outperforms typically used ppca model missing data links higher pscore values better recovered