Explicit rates of approximation in the CLT for quadratic forms
Friedrich G\"otze, Andrei Yu. Zaitsev

TL;DR
This paper establishes explicit, optimal rates of convergence in the Central Limit Theorem for quadratic forms of sums of i.i.d. random vectors in high dimensions, extending previous results to the case d≥5.
Contribution
It provides the first explicit bounds of order N^{-1} for the approximation of quadratic forms in the CLT for dimensions as low as 5, with precise constants.
Findings
Rate of convergence is O(N^{-1}) for quadratic forms in high dimensions.
Explicit bounds depend on the fourth moment and covariance structure.
Extends previous results to lower dimensions (d≥5).
Abstract
Let be i.i.d. -valued real random vectors. Assume that , , and that is not concentrated in a proper subspace of . Let be a mean zero Gaussian random vector with the same covariance operator as that of . We study the distributions of nondegenerate quadratic forms of the normalized sums and show that, without any additional conditions, \[\Delta_N\stackrel{\mathrm{def}}{=}\sup_x\bigl |\mathbf{P}\bigl\{\mathbb{Q}[S_N]\leq x\bigr\}-\mathbf{P}\bigl\{\mathbb{Q}[G]\leq x\bigr\}\bigr|={\mathcal{O}}\bigl(N^{-1}\bigr),\] provided that and the fourth moment of exists. Furthermore, we provide explicit bounds of order for for the rate of approximation by…
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