Research InterestsPrediction Theory and Time Series Analysis,
Analysis of Financial Data,
Multivariate Statistics(Longitudinal Data,Panel Data,etc)
Data mining,Classification and Clustering,
Modeling Covariance Matrices.
My current vita with publication list and other activities.
For two recent reviews of my book on Foundations of Time Series Analysis and Prediction Theory,Wiley(2001),see J.Andel and E.Parzen.They provide information about its coverage and objectives.Some of the datasets used in the book are: the famous lynx data, the snotel seriesand snow series.
The slides from my ASA-Chicago Chapter talk and subsequent improvements (PDF format)
1.Pourahmadi,M.,Daniels,M. and Park,T.(2007).Simultaneous Modelling of the Cholesky Decomposition of Several Covariance Matrice sJournal of Multivariate Analysis,98,568-587.
2.Huang,J.,Liu,N.,Pourahmadi,M.and Liu,X.(2006).Covariance selection and estimation via penalised normal likelihood. Biometrika,93,85-98.
5.Pourahmadi,M.,Inoue,A.and Kasahara,Y.(2007).A Prediction Problem in L2(w).Proceedings of Amer.Math Soc.135,1233-1239.
6. An extensive review of the history of modelling covariance matrices emphasizing the growth in the direction of generalized linear models(GLM) using variance-correlation,spectral(eigenvalue) and modified Cholesky decompositions.
7.A joint work with Petros Dellaportas using the modified Cholesky decomposition or contemporaneos ARMA models to parsimoniously parametrize high-dimensional volatility matrices arising in finance.