Differentially Private Log-Location-Scale Regression Using Functional Mechanism for Privacy-Preserving Prognostics

This article proposes differentially private log-location-scale (DP-LLS) regression models that incorporate differential privacy into LLS regression through the functional mechanism. The proposed models perturb the log-likelihood function of LLS regression to obtain privacy-preserving parameter estimates.