Dan (Daniela) Yang's  Home Page
Fifth Year Ph.D. Student 
Department of Statistics
The Wharton School
University of Pennsylvania

Contact:

Current Interests:

High dimensional statistical inference: with Andreas Buja and Zongming Ma

• Sparse SVD: the singular vectors are assumed to be sparse.
• Near optimal sparse SVD in high dimensions: A theoretical paper on minimax rate under normality assumptions.
• A sparse SVD method for high dimensional data: A methodological paper on a fast and data-driven algorithm that is robust to heavy-tailed distributions. [.pdf].
• Squared LASSO and sparse SVD:  Sparse SVD via unconstrained penalization. Talk slides
• Functional SVD: the singular vectors are assumed to be smooth.
• Optimal recovery of low rank matrix for functional data in high dimensionals.
• Presmoothing, postsmoothing, half-half-smoothing or other types of smoothing?
  

• Optimal matching with minimal deviation from fine balance: with Dylan Small, Jeffrey H. Silber, and Paul R. Rosenbaum. Biometrics. In press. [.pdf]. Assignment algorithm and network flow algorithm. [R Package] available on CRAN.
• Methods for computing empirical likelihood: involving convex optimization techniques. [R Package] available on CRAN.  [.pdf].
• Matched sampling for difference in difference (DID) study: with Dylan S. Small, Scott A. Lorch, and Sindhu K. Srinivas. Distance metric and simulated annealing algorithm.
• Validity of instrumental variables (IV): Over-identifying restriction tests for IV regression with heterogeneous treatment effect. 
• A study of bias in case-crossover analyses of chronic conditions.

Courses Finished:  

STAT 900 ADVANCED PROBABILITY: Probability Theory and Combinatorial Optimization 
STAT 999 INDEPENDENT STUDY: Matching Methods for Observational Study
STAT 999 INDEPENDENT STUDY: Machine Learning and Multivariate Analysis
STAT 921 OBSERVATIONAL STUDIES 
STAT 991 SEM IN ADV APPL OF STAT: Advance Research Topics
STAT 991 SEM IN ADV APPL OF STAT: High-Dimensional Inference 
STAT 999 INDEPENDENT STUDY: Machine Learning and Multivariate Analysis
STAT 553 MACHINE LEARNING
STAT 910 FORCAS & TIME SER ANALY
STAT 999 INDEPENDENT STUDY: Empirical Likelihood and Instrumental Variables
STAT 552 ADV TOPICS IN MATH STAT
STAT 920 SAMPLE SURVEY METHODS
STAT 955 STOCH CAL & FIN APPL
STAT 991 SEM IN ADV APPL OF STAT: Advance Research Topics
STAT 531 STOCHASTIC PROCESSES
STAT 542 BAYESIAN METH & COMP
STAT 551 INTRO TO LINEAR STAT MOD
STAT 530 PROBABILITY
STAT 541 STATISTICAL METHODS
STAT 550 MATHEMATICAL STATISTICS