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Profile
Xueying Tang
Member of the Graduate Faculty | Assistant Professor, Mathematics
Mathematics
Overview
Research
More
Collaboration
(1)
Sunder Sethuraman
Mutual work: 2 Publications
Collaboration Details
Grants
(1)
Statistical Methods for Response Process Data
Active
·
2023
·
$161.7K
·
External
Principal Investigator (PI)
statistical methods,
response process,
data analysis,
survey research,
psychometrics
Publications
(68)
Recent
Modeling sparsity with super heavy-tailed priors
2024
statistical modeling,
bayesian inference,
machine learning,
sparse data,
prior distribution
Response Process Signature
2024
signature verification,
authentication,
digital signatures,
document verification,
identity validation
Measurement error models with global-local priors for small area estimation
2023
measurement error,
small area estimation,
global-local priors,
statistical modeling,
bayesian inference
External Correlates of Adult Digital Problem-Solving Process: An Empirical Analysis of PIAAC PSTRE Action Sequences
2023
digital literacy,
adult education,
problem solving,
empirical analysis,
piaac pstre
Global-Local Priors for Spatial Small Area Estimation
2023
spatial statistics,
estimation methods,
data analysis,
geospatial analysis,
statistical modeling
Subtask analysis of process data through a predictive model
2023
predictive modeling,
process data,
subtask analysis,
data analysis,
machine learning
A latent hidden Markov model for response process data
2023
hidden markov model,
response process,
latent variable,
data modeling,
probabilistic modeling
A hierarchical gamma prior for modeling random effects in small area estimation
2023
hierarchical modeling,
random effects,
small area estimation,
gamma prior,
modeling
Multivariate global-local priors for small area estimation
2022
small area estimation,
multivariate priors,
global-local priors,
multivariate global-local priors,
estimation
Stationarity and Inference in Multistate Promoter Models of Stochastic Gene Expression via Stick-Breaking Measures
2022
gene expression,
stochastic modeling,
promoter models,
stationarity,
inference