Suneel Babu Chatla

Dr. Chatla's research focuses on developing methodologies for dependent data and high-dimensional data. His research interests include semi-parametric and non-parametric methods, generalized linear models and statistical computing.

KEYWORDS

• High-dimensional
• Nonparametric and semi parametric
• Generalized linear models
• Statistical computing
• Dependent data

Education

• Ph D in Statistics, National Tsing Hua University (2017)

Publications

• A Tree-based Semi-Varying Coefficient Model for the COM-Poisson Distribution, Journal of Computational and Graphical Statistics, 29 (4), (2020), Suneel Chatla, Galit Shmueli.
• Efficient estimation of COM–Poisson regression and a generalized additive model, Computational Statistics & Data Analysis, 12, (2018), Suneel Chatla, Galit Shmueli.
• An Extensive Examination of Regression Models with a Binary Outcome Variable, Journal of the Association for Information Systems, 18 (4), (2017), Suneel Babu Chatla, Galit Shmueli.
• Selected topics in statistical computing, Encyclopedia with Semantic Computing and Robotic Intelligence, 1 (1), (2017), Suneel Chatla, Galit Shmueli, Chun-houh Chen.

Presentations

• Nonparametric inference for additive models estimated via simplified smooth backfitting (2021), Suneel Chatla.

Grants

• Tree-based Bayesian methods for optimal treatment regimes