1 |
A. Rackauskas and C. Suquet, Invariance principles for adaptive self-normalized partial
sums processes, Stochastic Process. Appl. 95 (2001), no. 1, 63-81.
DOI
ScienceOn
|
2 |
Q. M. Shao, Almost sure invariance principles for mixing sequences of random variables,
Stochastic Process. Appl. 48 (1993), no. 2, 319-334.
DOI
ScienceOn
|
3 |
Q. M. Shao, An invariance principle for stationary sequence with infinite variance,
Chinese Ann. Math. Ser. B 14 (1993), no. 1, 27-42.
|
4 |
Q. M. Shao, Self-normalized large deviations, Ann. Probab. 25 (1997), no. 1, 285-328.
DOI
ScienceOn
|
5 |
W. Wang, Self-normalized lag increments of partial sums, Statist. Probab. Lett. 58
(2002), no. 1, 41-51.
DOI
ScienceOn
|
6 |
M. Peligrad, The convergence of moments in the central limit theorem for sequences of random variables, Proc. Amer. Math. Soc. 101 (1987), no. 1, 142-148.
|
7 |
M. Peligrad and Q. M. Shao, Estimation of the variance of partial sums for random variables, J. Multivariate Anal. 52 (1995), no. 1, 140-157.
DOI
ScienceOn
|
8 |
N. H. Bingham, C. M. Goldie, and J. L. Teugels, Regular Variation, Cambridge University Press, Cambridge, 1987.
|
9 |
R. Balan and R. Kulik, Weak invariance principle for mixing sequences in the domain
of attraction of normal law, Studia Sci. Math. Hungarica 46 (2009), no. 3, 329-343.
|
10 |
R. Balan and I. M. Zamfirescu, Strong approximation for mixing sequences with infinite
variance, Electron. Comm. Probab. 11 (2006), 11-23.
DOI
|
11 |
R. C. Bradley, A central limit theorem for stationary sequences with infinite
variance, Ann. Probab. 16 (1988), no. 1, 313-332.
DOI
ScienceOn
|
12 |
M. Csorgo, Z. Y. Lin, and Q. M. Shao, Studentized increments of partial sums, Sci.
China Ser. A. 37 (1994), no. 3, 265-276.
|
13 |
M. Csorgo, B. Szyszkowicz, and Q. Wang, Donsker's theorem for self-normalized partial
sums processes, Ann. Probab. 31 (2003), no. 3, 1228-1240.
DOI
ScienceOn
|
14 |
N. Etemadi, On some classical results in probability theory, Sankhya Ser. A 47 (1985),
no. 2, 215-221.
|
15 |
P. Griffin and J. Kuelbs, Some extensions of the LIL via self-normalizations, Ann.
Probab. 19 (1991), no. 1, 380-395.
DOI
ScienceOn
|
16 |
Z. Y. Lin and C. R. Lu, Limit Theory for Mixing Dependent Random Variables, Kluwer
Academic Publishers, Dordrecht; Science Press, New York, 1996.
|