- Research Article
- Open Access
Doob's Type Inequality and Strong Law of Large Numbers for Demimartingales
© Wang Xuejun et al. 2010
- Received: 9 October 2009
- Accepted: 28 January 2010
- Published: 21 February 2010
We establish some maximal inequalities for demimartingales which generalize the result of Wang (2004). The maximal inequality for demimartingales is used as a key inequality to establish other results including Doob's type maximal inequality, strong law of large numbers, strong growth rate, and integrability of supremum for demimartingales, which generalize and improve partial results of Christofides (2000) and Prakasa Rao (2007).
- Growth Rate
- Real Number
- Variable Sequence
- Partial Result
- Strong Growth
for all coordinatewise nondecreasing functions such that the expectation is defined. Then is called a demimartingale. If in addition the function is assumed to be nonnegative, then the sequence is called a demisubmartingale.
for any two coordinatewise nondecreasing functions on such that the covariance is defined. An infinite sequence is associated if every finite subcollection is associated.
An infinite sequence is strongly positive dependent if every finite subcollection is strongly positive dependent.
Chow  proved a maximal inequality for submartingales. Newman and Wright  extended Doob's maximal inequality and upcrossing inequality to the case of demimartingales, and pointed out that the partial sum of a sequence of mean zero associated random variables is a demimartingale. Christofides  showed that the Chow's maximal inequality for (sub)martingales can be extended to the case of demi(sub)martingales. Wang  obtained Doob's type inequality for more general demimartingales. Hu et al.  gave a strong law of large numbers and growth rate for demimartingales. Prakasa Rao  established some maximal inequalities for demisubmartingales and N-demisuper-martingales.
It is easily seen that the partial sum of a sequence of mean zero strongly positive dependent random variables is also a demimartingale by the inequality (3) in Zheng , that is, for all ,
for all coordinatewise nondecreasing functions such that the expectation is defined. Therefore, the main results of this paper hold for the partial sums of sequences of mean zero associated random variables and strongly positive dependent random variables.
Let and be sequences of random variables defined on a fixed probability space and the indicator function of the event . Denote , , , , . The main results of this paper depend on the following lemmas.
Lemma 1.5 (see Wang [4, Theorem ]).
If is a demisubmartingale (or a demimartingale) and is a nondecreasing convex function such that , then is a demisubmartingale.
If is a demimartingale, then is a demisubmartingale and is a demisubmartingale.
Lemma 1.8 (see Hu et al. [9, Theorem ]).
Let be a demisubmartingale. Then for any ,
Let be a demisubmartingale and a nonincreasing sequence of positive numbers. Then for any ,
Using Lemma 1.5, Wang  obtained the following inequalities for demimartingales.
Theorem 1.10 (see Wang [4, Corollary ]).
We point out that there is a mistake in the proof of (1.17), that is,
should be replaced by
In fact, by Lemma 1.5 and Fubini Theorem, we can see that
The rest of the proof is similar to Corollary in Wang .
in Shiryaev [10, page 495] should be revised as
Thus, (2.2) follows from (2.8) immediately. The proof is complete.
If we take in Theorem 2.1, then Theorem 2.1 implies Corollary 2.1 in Wang .
Corollary 2.4 (Doob's type maximal inequality for demimartingales).
Therefore, follows from Lemma 1.6, (2.16), and (2.17); (1.9), (1.10), (2.14), (2.15) hold. This completes the proof of the theorem.
In Theorem 2.5, if we assume that is a nonnegative and nondecreasing convex function on with , then the condition " for each " is satisfied.
Therefore, (2.22) follows from the above statements immediately.
By Corollary 2.9, we can get the following theorem.
Similar to the proof of Theorem 2.8 and using Lemma 1.9(i), we can get the following.
Let be a nonnegative demisubmartingale. Then for all , .
The authors are most grateful to the Editor Andrei Volodin and an anonymous referee for the careful reading of the manuscript and valuable suggestions which helped in significantly improving an earlier version of this paper. This work was supported by the National Natural Science Foundation of China (Grant no. 10871001, 60803059), Talents Youth Fund of Anhui Province Universities (Grant no. 2010SQRL016ZD), Youth Science Research Fund of Anhui University (Grant no. 2009QN011A), Provincial Natural Science Research Project of Anhui Colleges and the Innovation Group Foundation of Anhui University.
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