Mathematical Sciences: Time Series, Extreme Values and Stochastic Models

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The research to be carried out under this award is divided into three parts. Part A is concerned with problems of estimation and prediction for time series models whose theory is not fully understood. These include nonlinear, heavy tailed and non-Gaussian processes, all of which play an important role in the modelling of real time series data. The second Part deals with extreme value theory, and the application of ideas from point processes to analysis of linear, bilinear and generally stationary processes. Results of the second part will help in a better analysis of the first part. Part C is concerned with processes arising in the modelling of storage systems and population growth.