Abstract
Large sample theory, also called asymptotic theory, is used to approximate the distribution of an estimator when the sample size n is large. This theory is extremely useful if the exact sampling distribution of the estimator is complicated or unknown. To use this theory, one must determine what the estimator is estimating, the rate of convergence, the asymptotic distribution, and how large n must be for the approximation to be useful. Moreover, the (asymptotic) standard error (SE), an estimator of the asymptotic standard deviation, must be computable if the estimator is to be useful for inference.
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Olive, D.J. (2014). Large Sample Theory. In: Statistical Theory and Inference. Springer, Cham. https://doi.org/10.1007/978-3-319-04972-4_8
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