Published articles

• Debashis Paul (2004) - Discussion on "Statistical approaches to inverse problems", Journal of the Royal Statistical Society, Series B, Vol. 66, pp. 634-635



• Debashis Paul (2005) - Nonparametric estimation of principal components , Ph.D. Thesis, Stanford University, Department of Statistics



• Ping Li, Debashis Paul, Ravi Narasimhan and John Cioffi (2006) - On the distribution of SINR for the MMSE MIMO receiver and performance analysis, IEEE Transactions on Information Theory, Vol. 52, No. 1, pp. 271-286. [Technical Report]



• Eric Bair, Trevor Hastie, Debashis Paul and Robert Tibshirani (2006) - Prediction by supervised principal components, Journal of the American Statistical Association, Vol. 101, No. 473, pp. 119-137. [Technical Report (September, 2004 version)]



• Debashis Paul (2007) - Asymptotics of sample eigenstruture for a large dimensional spiked covariance model, Statistica Sinica, Vol. 17, No. 4, pp. 1617-1642. [Technical Report (June, 2005 version)]



• Debashis Paul, Eric Bair, Trevor Hastie and Rob Tibshirani (2006) - Pre-conditioning for feature selection and regression in high-dimensional problems , (Technical report). To appear in Annals of Statistics.



• Debashis Paul and Jack W. Silverstein (2007) - No eigenvalues outside the support of limiting empirical spectral distribution of a separable covariance matrix , (Technical report). To appear in Journal of Multivariate Analysis.



• Debashis Paul and Jie Peng (2007) - Consistency of restricted maximum likelihood estimators of principal components , (Technical report). To appear in Annals of Statistics.

Technical reports

• Debasis Sengupta and Debashis Paul (2004) - Some tests for logconcavity of life distributions , (under revision).



• Tomoko Matsuo, Doug Nychka and Debashis Paul (2006) - Nonstationary covariance modeling for incomplete data : smoothed Monte-carlo EM approach , (under revision).



• Jie Peng and Debashis Paul (2007) - A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data , (submitted).



• Anandamayee Majumdar, Debashis Paul and Dianne Bautista (2007) - A generalized convolution model for multivariate nonstationary spatial processes , (submitted).

Working papers

• Debashis Paul and Iain Johnstone (2007) - Sparse principal component analysis for high dimensional data.



• Jie Peng and Debashis Paul (2007) - Covariance estimation for sparse irregular longitudinal data using a kernel smoothing approach.