Mathematical Sciences: Strong Approximations of the Distributions of Estimators in Linear Stochastic Models

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The research for this project is directed at establishing suitable approximations to the distributions of estimators of parameters in linear stochastic models. By approximations, Berry.Essen bounds and asymptotic expansions are also included. The method that will be used will be different from the usual method of characteristic functions and will also give approximations uniformly over all Borel subsets, which is also one of the aims of the project. Some specific statistical models that will be considered in detail include nonlinear regression, autoregression, regression with lagged dependent variables. Robust versions of the estimators in these models will be considered in addition to the least squares estimators.