I joined the Department of Biostatistics and Bioinformatics at the George Washington University as an assistant professor in the Fall of 2023. I completed my Ph.D. from the Department of Statistics at the University of Michigan, Ann Arbor. I worked as a post-doctoral researcher at the Department of Mathematics at Ruhr Universitat Bochum, Germany, for three years. I am interested in developing statistical methodology for analyzing longitudinal, spatial, and time series data focusing on high dimensional and functional observations. Please visit my research page for more details about my research and publications.
I am always looking for new and interesting opportunities for collaboration. Please get in touch with me if you are interested in collaborating on a research project.
➤ LOCATION
Science & Engineering Hall 800 22nd Street, NW
Washington, DC - 20052
☎ CONTACT
pramita.bagchi@gwu.edu
(703) 362-5635
Research
My primary research interest is modelling and analyzing dependent data. Dependence among observed data is a phenomenon that arises naturally in important problems, especially in time series and spatial data. I am specifically interested in large complex objects, e.g. functional time series data or spatial surface data, which has emerged as an important object of interest in statistics with the availability of high-dimensional and high-resolution data in recent years. A detailed description of my research is available here. Some of my current interests are:
Functional Data
Time Series Data
Spatial Statistics
Shape Constrained Inference
Asymptotic Theory
Empirical Processes
Long Range Dependence
Non-parametric Inference
Publication
Some of my recent and important publications are listed here. For a full list please visit here.
James Cameron and Pramita Bagchi (2021) Test for heteroscedasticity in functional linear models. Test. [pdf]
Pramita Bagchi and Holger Dette (2020). "A Test for Separability in Covariance Operators of Random Surfaces. The Annals of Statistics, Vol: 48(4), page: 2303–2322. [pdf]
Pramita Bagchi and Subhra Sankar Dhar (2020). "A Study on the Least Square Estimator of Multivariate Isotonic Regression Function." Scandinavian Journal of Statistics, to appear. [pdf]
Pramita Bagchi, Vaidotas Characiejus and Holger Dette (2018), "A Simple Test for White Noise in Functional Time Series." Journal of Time Series Analysis, Vol 39, page: 54 - 74 . [pdf]
Pramita Bagchi, Moulinath Banerjee and Stilian Stoev (2016). "Inference for Monotone Functions Under Short-and Long-Range Dependence: Confidence Intervals and New Universal Limits." Journal of the American Statistical Association, Vol: 111(516), page: 1634-1647. [pdf]
Teaching
I am teaching Mathematical Statistics I (STAT 872) this semester. Visit here to find a full description of the courses I have taught.
Contact
Please feel free to get in touch with me if you are interested in my research. I welcome any exciting opportunity to collaborate on both methodological and applied projects.