

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 talk given at the Bayesian Focus Week , SAMSI,Oct.30Nov.3,2006.. The slides from my ASAChicago Chapter talk and subsequent improvements (PDF format) Recent Preprints
1.Pourahmadi,M.,Daniels,M. and Park,T.(2007).Simultaneous Modelling of the Cholesky Decomposition of Several Covariance Matrice sJournal of Multivariate Analysis,98,568587.
2.Huang,J.,Liu,N.,Pourahmadi,M.and Liu,X.(2006).Covariance selection and estimation via penalised normal likelihood. Biometrika,93,8598.
3.Pourahmadi,M.(2006).Cholesky Decompositions and Estimation of a Covariance Matrix:Orthogonality of VarianceCorrelation Parameters.
4.Pourahmadi,M.(2005).SkewNormal Time Series Models With Nonlinear Heteroscedastic Predictors.Special Issue of Communication in Statistics,to appear.
5.Pourahmadi,M.,Inoue,A.and Kasahara,Y.(2007).A Prediction Problem in L2(w).Proceedings of Amer.Math Soc.135,12331239.
6. An extensive review of the history of modelling covariance matrices emphasizing the growth in the direction of generalized linear models(GLM) using variancecorrelation,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 highdimensional volatility matrices arising in finance. 8.An expository and review paper on skewnormal distributions. 
