Quadratic distances on probabilities: A unified foundation (2008)
Lindsay, Bruce G., Markatou, Marianthi, Ray, Surajit, Yang, Ke, Chen, Shu-Chuan
This work builds a unified framework for the study of quadratic form distance measures as they are used in assessing the goodness of fit of models. Many important procedures have this structure, but...
Lin, Hong, Ray, Surajit, Tongchusak, Songsak, Reinherz, Ellis L, Brusic, Vladimir
Abstract Background Protein antigens and their specific epitopes are formulation targets for epitope-based vaccines. A number of prediction servers are available for identification of peptides that...
Ray, Surajit, Kepler, Thomas B
Abstract Background A key step in the development of an adaptive immune response to pathogens or vaccines is the binding of short peptides to molecules of the Major Histocompatibility Complex (MHC)...
Model selection in High-Dimensions: A Quadratic-risk based approach (2006)
Ray, Surajit, Lindsay, Bruce G.
In this article we propose a general class of risk measures which can be used for data based evaluation of parametric models. The loss function is defined as generalized quadratic distance between...
The topography of multivariate normal mixtures (2006)
Ray, Surajit, Lindsay, Bruce G.
Multivariate normal mixtures provide a flexible method of fitting high-dimensional data. It is shown that their topography, in the sense of their key features as a density, can be analyzed rigorously...
The topography of multivariate normal mixtures (2005)
Ray, Surajit, Lindsay, Bruce G.
Multivariate normal mixtures provide a flexible method of fitting high-dimensional data. It is shown that their topography, in the sense of their key features as a density, can be analyzed rigorously...
ia State University 2001--2003 Computer Support Group, Dept. of Statistics, Pennsylvania State University. 2001--2002 Instructor, Dept. of Statistics, Pennsylvania State University 2000--2001...
Distance-based Model-Selection with application to the Analysis of Gene Expression Data (2003)
Multivariate mixture models provide a convenient method of density estimation and model based clustering as well as providing possible explanations for the actual data generation process. But the...
Distance-based model-selection with application to the analysis of gene expression data (2003)
Thesis (Ph. D.)--Pennsylvania State University, 2003.
Distance-based model-selection with application to the analysis of gene expression data (2003)
Thesis (Ph. D.)--Pennsylvania State University, 2003.
Introduction The basic set-up of Goodness of Fit tests are as follows For a sequence of n observations on a multinomial distribution with k cells Denote the probability vector by p, p 1 p k , i 1 p i...
Improved Power in Multinomial Goodness-of-fit Tests (2002)
Ayanendranath Basu, Surajit Ray
this paper we try to explain why the above behavior of the power divergence test statistics are natural, and make a preliminary attempt to provide some new tests with reasonably high power at both...
Surajit Ray, B. Ravikumar, N. Eugene Savin
In this paper, we examine the robust Wald test statistic for SUR systems with adding up restrictions where the same explanatory variables are present in all equations and where heteroskedasticity...
This paper illustrates the pitfalls of the conventional heteroskedasticity and autocorrelation robust (HAR) Wald test and the advantages of new HAR tests developed by Kiefer and Vogelsang in 2005 and...
Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research
Lin, Hong Huang, Ray, Surajit, Tongchusak, Songsak, Reinherz, Ellis L, Brusic, Vladimir
CAPM Reconsidered: A Robust Finite Sample Evaluation
Ravikumar, B., Ray, Surajit, Savin, N.E.
In this paper, the conventional test of the Sharpe-Lintner version of the Capital Asset Pricing Model (CAPM) are reconsidered. The CAPM is formulated as a Seemingly Unrelated Regression (SUR) system...
Model selection in high dimensions: a quadratic-risk-based approach
We propose a general class of risk measures which can be used for data-based evaluation of parametric models. The loss function is defined as the generalized quadratic distance between the true...