On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models

We consider estimating the parametric components of semi-parametric multiple index models in a high-dimensional and non-Gaussian setting. Such models form a rich class of non-linear models with applications to signal processing, machine learning and statistics. Our estimators leverage the score function based first and second-order Stein's identities and do not require the covariates to satisfy Gaussian or elliptical symmetry assumptions common in the literature. Moreover, to handle score functions and responses that are heavy-tailed, our estimators are constructed via carefully thresholding their empirical counterparts. We show that our estimator achieves near-optimal statistical rate of convergence in several settings. We supplement our theoretical results via simulation experiments that confirm the theory

Additional file 5: Table S4. of Comparative analysis of gut microbiota associated with body mass index in a large Korean cohort

Comparison of regression analysis with or without adjustment of T2DM or T2DM under medication as covariates. (DOCX 19 kb

MOESM1 of Establishment and characterization of 6 novel patient-derived primary pancreatic ductal adenocarcinoma cell lines from Korean pancreatic cancer patients

Additional file 1: Figure S1. TP53 histogram of AMCPAC cell lines

Additional file 1: of Efficacy and safety of indacaterol/glycopyrronium fixed-dose combination in mild-to-moderate COPD patients symptomatic on tiotropium in Korea: study protocol for a randomized controlled trial

List of participating centers in Korea. (DOC 63 kb

Additional file 1: Table S1. of Predicting survival of patients with idiopathic pulmonary fibrosis using GAP score: a nationwide cohort study

Comorbidities of idiopathic pulmonary fibrosis patients according to GAP score. Table S2. Initial presenting symptoms of study population. Table S3. Survival analysis with Cox proportional hazard model including age, sex, FVC (%), DLCO (%), and smoking. (DOCX 23 kb

Additional file 1: Table S1. of Factors affecting treatment outcome in patients with idiopathic nonspecific interstitial pneumonia: a nationwide cohort study

Treatment modality in treatment group (n = 86). Table S2. Comorbidities of study population. Table S3. Comparison between initial and 1-year follow-up lung function according to treatment. Table S4. Analysis of risk factors that associated with treatment failure (by logistic regression). (DOCX 26 kb