T. Savitsky

发表

Bayesian hierarchical semiparametric modelling of longitudinal post‐treatment outcomes from open enrolment therapy groups

S. Paddock, T. Savitsky, 2013, Journal of the Royal Statistical Society. Series A,.

Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.

Marina Vannucci, Naijun Sha, Terrance Savitsky, 2011, Statistical science : a review journal of the Institute of Mathematical Statistics.

Spiked Dirichlet Process Priors for Gaussian Process Models.

Marina Vannucci, Terrance Savitsky, M. Vannucci, 2010, Journal of probability and statistics.

Generalized Gaussian process models with Bayesian variable selection

Terrance D. Savitsky, T. Savitsky, 2010 .

Collaborative learning framework for online stakeholder engagement

Terrance D. Savitsky, Siddhartha Dalal, Dmitry Khodyakov, 2015, Health expectations : an international journal of public participation in health care and health policy.

Convergence of Pseudo Posterior Distributions under Informative Sampling

Daniell Toth, T. Savitsky, 2015 .

Developing a Research Strategy for Suicide Prevention in the Department of Defense: Status of Current Research, Prioritizing Areas of Need, and Recommendations for Moving Forward.

R. Ramchand, E. Pedersen, T. Tanielian, 2014, Rand health quarterly.

Model-Based Screening for Robust Estimation in the Presence of Deviations from Linearity in Small Domain Models

T. Savitsky, J. Gershunskaya, 2020, Journal of Survey Statistics and Methodology.

Distributed Bayesian Inference in Massive Spatial Data

Sanvesh Srivastava, Cheng Li, Rajarshi Guhaniyogi, 2023, Statistical Science.

Bayesian Data Synthesis and Disclosure Risk Quantification: An Application to the Consumer Expenditure Surveys

T. Savitsky, Jingchen Hu, 2018, Trans. Data Priv..

Joint Point and Variance Estimation under a Hierarchical Bayesian model for Survey Count Data

T. Savitsky, J. Gershunskaya, M. Crankshaw, 2022, 2210.14366.

Bayesian Mixed Effects Model Estimation under Informative Sampling

Matthew R. Williams, T. Savitsky, 2019, 1904.07680.

Fully Bayesian estimation under informative sampling

L. León-Novelo, T. Savitsky, 2017, Electronic Journal of Statistics.

BAYESIAN NONPARAMETRIC MULTIRESOLUTION ESTIMATION FOR THE AMERICAN COMMUNITY SURVEY BY TERRANCE

T. Savitsky, D. Savitsky, 2017 .

The frequency and cost of treatment perceived to be futile in critical care.

Thanh N. Huynh, N. Wenger, J. Wiley, 2013, JAMA internal medicine.

Risk-Efficient Bayesian Data Synthesis for Privacy Protection

Terrance D. Savitsky, Jingchen Hu, Matthew R. Williams, 2019, Journal of Survey Statistics and Methodology.

Dependent Latent Effects Modeling for Survey Estimation with Application to the Current Employment Statistics Survey

Julie Gershunskaya, Terrance D. Savitsky, T. Savitsky, 2017 .

Bayesian Non-Parametric Hierarchical Modeling for Multiple Membership Data in Grouped Attendance Interventions.

Susan M Paddock, Terrance D Savitsky, S. Paddock, 2013, The annals of applied statistics.

Bayesian Hierarchical Multivariate Formulation with Factor Analysis for Nested Ordinal Data

Daniel F McCaffrey, Terrance D Savitsky, D. McCaffrey, 2013, Psychometrika.

Bayesian Estimation Under Informative Sampling

Terrance D. Savitsky, Daniell Toth, Daniell Toth, 2015, 1507.07050.

Uncovering Multivariate Structure in Classroom Observations in the Presence of Rater Errors

Terrance D. Savitsky, Kun Yuan, Daniel F. McCaffrey, 2015 .

Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy

Matthew R. Williams, T. Savitsky, Jingchen Hu, 2019, J. Mach. Learn. Res..

Uncertainty Estimation for Pseudo‐Bayesian Inference Under Complex Sampling

Matthew R. Williams, Terrance D. Savitsky, Matthew R. Williams, 2020, International Statistical Review.

Bayesian Estimation Under Informative Sampling with Unattenuated Dependence

Terrance D. Savitsky, Matthew R. Williams, Matthew R. Williams, 2018, Bayesian Analysis.

Scalable Bayes under Informative Sampling

Terrance D. Savitsky, Sanvesh Srivastava, Sanvesh Srivastava, 2016, 1606.07488.

Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior

Sanvesh Srivastava, Cheng Li, Rajarshi Guhaniyogi, 2020, J. Mach. Learn. Res..

Private Tabular Survey Data Products through Synthetic Microdata Generation

Matthew R. Williams, T. Savitsky, Jingchen Hu, 2021, 2101.06188.

Optimization of Survey Weights under a Large Number of Conflicting Constraints

Terrance D. Savitsky, Matthew R. Williams, Matthew R. Williams, 2019, 1901.03791.

Mechanisms for Global Differential Privacy under Bayesian Data Synthesis

Matthew R. Williams, T. Savitsky, Jingchen Hu, 2022, Statistica Sinica.

A Divide-and-Conquer Bayesian Approach to Large-Scale Kriging

Cheng Li, Terrance D. Savitsky, Sanvesh Srivastava, 2017, 1712.09767.

The growclusters Package for R

T. Savitsky, Randall Powers, Wendy Martinez, 2023, ArXiv.

Creating a Data-Driven Taxonomy

T. Savitsky, Randall Powers, Wendy Martinez, 2021 .

Integration of Two RShiny Applications into the growclusters Package with and Example Implementation

T. Savitsky, Randall Powers, Wendy Martinez, 2020 .

Derivation of outcome-dependent dietary patterns for low-income women obtained from survey data using a Supervised Weighted Overfitted Latent Class Analysis

T. Savitsky, Stephanie M. Wu, Matthew R. Williams, 2023, 2310.01575.

Bayesian non‐parametric analysis of multirater ordinal data, with application to prioritizing research goals for prevention of suicide

Terrance D. Savitsky, Siddhartha R. Dalal, S. Dalal, 2014 .

Optimization for Calibration of Survey Weights under a Large Number of Conflicting Constraints

T. Savitsky, Matthew R. Williams, 2024, Journal of Computational and Graphical Statistics.

The frequency and cost of treatment perceived to be futile in critical care.

Thanh N. Huynh, N. Wenger, J. Wiley, 2013, JAMA internal medicine.

Between Large-N and Small-N Analyses: Historical Comparison of Thirty Insurgency Case Studies

Christopher Paul, Colin P. Clarke, Beth Grill, 2013 .

Bayesian Dependent Functional Mixture Estimation for Area and Time-Indexed Data: An Application for the Prediction of Monthly County Employment

Matthew R. Williams, T. Savitsky, 2021 .

Distributed Bayesian Kriging

Sanvesh Srivastava, Rajarshi Guhaniyogi, T. Savitsky, 2021 .