Abstract
In this chapter, we start by giving upper bounds for algebraic moments of partial sums from a strongly mixing sequence. These inequalities are similar to Rosenthal’s inequalities (Rosenthal, Israel J Math, 8:273–303, 1970) concerning moments of sums of independent random variables.
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Exercises
Exercises
(1) Let \((X_{i})_{i\in {\mathrm{Z\!\!\;\!\! Z}}}\) be a sequence of centered real-valued random variables with finite fourth moments, and let \((\alpha _n)_{n\ge 0}\) be defined by (2.1).
(a) Let \(i \le j \le k \le l\) be natural integers. Prove that
(b) Prove that
(c) Prove that
(d) Suppose now that \(\Vert X_k \Vert _\infty \le 1\) for any k in [1, n]. Derive from the above inequalities that
Compare (3) with (2.13) and (2.11).
(2) Let \((S_n)_{n \ge 0}\) be a martingale sequence in \(L^p\) for some \(p>2\) and \(X_n = S_n - S_{n-1}\). Either use Inequality (2.3) in Pinelis (1994) or adapt the proof of Theorem 2.5 to prove the inequality (4) below, given in Rio (2009):
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Rio, E. (2017). Algebraic Moments, Elementary Exponential Inequalities. In: Asymptotic Theory of Weakly Dependent Random Processes. Probability Theory and Stochastic Modelling, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54323-8_2
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DOI: https://doi.org/10.1007/978-3-662-54323-8_2
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