I’ve worked on a variety of topics including non-parametric penalized
likelihood estimation, the EM algorithm, simulated annealing, and third
moment tensor methods.
Articles
- W. D. Brinda and Ruchira Ray. The third moment tensor method with
principal components and basis expansion. JSM Proceedings, 2022
(pdf
| code)
- W. D. Brinda, Jason Klusowski, and Dana Yang. Hölder’s identity.
Statistics and Probability Letters, 2019.
- Jason Klusowski, Dana Yang, and W. D. Brinda. Estimating the coefficients
of a mixture of two linear regressions by expectation maximization.
IEEE Transactions on Information Theory, 2019
- W. D. Brinda. Adaptive Estimation with Gaussian Radial Basis
Mixtures. PhD thesis, Yale University, 2018. (pdf
| code)
- W. D. Brinda and Jason M. Klusowski. Finite-sample risk bounds for
maximum likelihood estimation with arbitrary penalties. IEEE
Transactions on Information Theory, 2018.
- W. D. Brinda, Shantanu Jain, and Michael Trosset. Inference on
random graphs with classified edge attributes. Indiana University
Department of Statistics Technical Report 11-03, 2011.