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Uniformly Accurate Quantile Bounds Via The Truncated Moment Generating Function: The Symmetric Case

  
@article{EJP452,
	author = {Michael Klass and Krzysztof Nowicki},
	title = {Uniformly  Accurate Quantile Bounds Via The Truncated Moment Generating Function: The Symmetric Case},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {12},
	year = {2007},
	keywords = {Sum of independent rv's, tail distributions, tail distributions,tail probabilities, quantile approximation,  Hoffmann-Jo rgensen/Klass-Nowicki Inequality},
	abstract = {Let $X_1, X_2, \dots$ be independent and symmetric random variables  such that $S_n = X_1 + \cdots + X_n$ converges to a finite valued random variable $S$ a.s. and let $S^* = \sup_{1 \leq n \leq \infty} S_n$ (which is finite a.s.).  We construct upper and lower bounds for $s_y$ and $s_y^*$, the upper $1/y$-th quantile of $S_y$ and $S^*$, respectively.  Our approximations rely on an explicitly computable quantity $\underline q_y$ for which we prove that $$\frac 1 2 \underline q_{y/2} < s_y^* < 2 \underline q_{2y} \quad \text{  and } \quad \frac 1 2 \underline q_{ (y/4) ( 1 + \sqrt{ 1 - 8/y})} < s_y < 2 \underline q_{2y}. $$ The RHS's  hold for  $y \geq 2$ and the LHS's for $y  \geq  94$ and $y \geq 97$, respectively. Although our results are derived primarily for symmetric  random variables, they apply to non-negative variates and extend to an absolute value of a sum of independent but otherwise arbitrary random variables.},
	pages = {no. 47, 1276-1298},
	issn = {1083-6489},
	doi = {10.1214/EJP.v12-452},    
        url = {http://ejp.ejpecp.org/article/view/452}}