Acknowledgement
The authors would like to thank the anonymous referees sincerely for their valuable comments. This work was supported by General Project of Natural Science Foundation of Chongqing (No. CSTB2022NSCQ-MSX1370), the Planning Topics Key Project for 13th Five-Year Plan of Chongqing Education Sciences (No. 2019-GX-118), and the SCR of Chongqing Municipal Education Commission (No. KJZD-M202100801).
References
- R. C. Bradley Jr., Introduction to Strong Mixing Conditions. Vol. 1, Kendrick Press, Heber City, UT, 2007.
- W. Bryc and A. Dembo, Large deviations and strong mixing, Ann. Inst. H. Poincare Probab. Statist. 32 (1996), no. 4, 549-569.
- A. V. Bulinski, Conditional central limit theorem, Theory Probab. Appl. 61 (2017), no. 4, 613-631, 61 (2016), no. 4, 686-708. https://doi.org/10.1137/S0040585X97T98837X
- T. C. Christofides and M. Hadjikyriakou, The conditional convex order and a comparison inequality, Stoch. Anal. Appl. 33 (2015), no. 2, 259-270. https://doi.org/10.1080/07362994.2014.984077
- D. D. Cox and T. Y. Kim, Moment bounds for mixing random variables useful in nonparametric function estimation, Stoch. Process. their Appl. 56 (1995), no. 1, 151-158. https://doi.org/10.1016/0304-4149(94)00063-Y
- M. Ekstrom, A general central limit theorem for strong mixing sequences, Statist. Probab. Lett. 94 (2014), 236-238. https://doi.org/10.1016/j.spl.2014.07.024
- S. Khovansky and O. Zhylyevskyy, On the consistency of a cross-sectional GMM estimator in the presence of an observable stochastic common data shock, Statist. Probab. Lett. 129 (2017), 196-202. https://doi.org/10.1016/j.spl.2017.05.017
- J. H. Lee and K. Song, Stable limit theorems for empirical processes under conditional neighborhood dependence, Bernoulli 25 (2019), no. 2, 1189-1224. https://doi.org/10.3150/17-bej1018
- F. Merlevade and M. Peligrad, The functional central limit theorem under the strong mixing condition, Ann. Probab. 28 (2000), no. 3, 1336-1352. https://doi.org/10.1214/aop/1019160337
- M. Ordonez Cabrera, A. Rosalsky, and A. Volodin, Some theorems on conditional mean convergence and conditional almost sure convergence for randomly weighted sums of dependent random variables, TEST 21 (2012), no. 2, 369-385. https://doi.org/10.1007/s11749-011-0248-0
- M. Peligrad, On the central limit theorem for weakly dependent sequences with a decomposed strong mixing coefficient, Stochastic Process. Appl. 42 (1992), no. 2, 181-193. https://doi.org/10.1016/0304-4149(92)90034-N
- B. L. S. Prakasa Rao, Conditional independence, conditional mixing and conditional association, Ann. Inst. Statist. Math. 61 (2009), no. 2, 441-460. https://doi.org/10.1007/s10463-007-0152-2
- D. Radulovic, The bootstrap of the mean for strong mixing sequences under minimal conditions, Statist. Probab. Lett. 28 (1996), no. 1, 65-72. https://doi.org/10.1016/0167-7152(95)00085-2
- M. Rosenblatt, A central limit theorem and a strong mixing condition, Proc. Nat. Acad. Sci. U.S.A. 42 (1956), no. 1, 43-47. https://doi.org/10.1073/pnas.42.1.43
- G. G. Roussas, On conditional independence, mixing, and association, Stoch. Anal. Appl. 26 (2008), no. 6, 1274-1309. https://doi.org/10.1080/07362990802405836
- A. Sheikhi, V. Amirzadeh, and R. Mesiar, A comprehensive family of copulas to model bivariate random noise and perturbation, Fuzzy Sets Syst. 415 (2021), 27-36. https://doi.org/10.1016/j.fss.2020.04.010
- M. Sood and O. Ya˘gan, On the minimum node degree and k-connectivity in inhomogeneous random K-out graphs, IEEE Trans. Inf. Theory 67 (2021), no. 10, 6868-6893. https://doi.org/10.1109/TIT.2021.3082854
- X. Wang and S. Hu, Conditional mean convergence theorems of conditionally dependent random variables under conditions of integrability, Front. Math. China 10 (2015), no. 3, 681-696. https://doi.org/10.1007/s11464-015-0450-6
- R. E. Welsch, A weak convergence theorem for order statistics from strong-mixing processes, Ann. Math. Statist. 42 (1971), no. 5, 1637-1646. https://doi.org/10.1214/aoms/1177693162
- S. C. Yang, Maximal moment inequality for partial sums of strong mixing sequences and application, Acta Math. Sin. (Engl. Ser.) 23 (2007), no. 6, 1013-1024. https://doi.org/10.1007/s10114-005-0841-9
- R. Yokoyama, Moment bounds for stationary mixing sequences, Z. Wahrsch. Verw. Gebiete 52 (1980), no. 1, 45-57. https://doi.org/10.1007/BF00534186
- K. Yoshihara, The Borel-Cantelli lemma for strong mixing sequences of events and their applications to LIL, Kodai Math. J. 2 (1979), no. 2, 148-157. http://doi.org/10.2996/kmj/1138036012
- D.-M. Yuan, J. An, and X.-S. Wu, Conditional limit theorems for conditionally negatively associated random variables, Monatsh. Math. 161 (2010), no. 4, 449-473. https://doi.org/10.1007/s00605-010-0196-x
- D.-M. Yuan and L. Lei, Some conditional results for conditionally strong mixing sequences of random variables, Sci. China Math. 56 (2013), no. 4, 845-859. https://doi.org/10.1007/s11425-012-4554-0
- D.-M. Yuan, L.-R. Wei, and L. Lei, Conditional central limit theorems for a sequence of conditional independent random variables, J. Korean Math. Soc. 51 (2014), no. 1, 1-15. https://doi.org/10.4134/JKMS.2014.51.1.001
- D.-M. Yuan and Y. Xie, Conditional limit theorems for conditionally linearly negative quadrant dependent random variables, Monatsh. Math. 166 (2012), no. 2, 281-299. https://doi.org/10.1007/s00605-012-0373-1
- D.-M. Yuan and Y.-K. Yang, Conditional versions of limit theorems for conditionally associated random variables, J. Math. Anal. Appl. 376 (2011), no. 1, 282-293. https://doi.org/10.1016/j.jmaa.2010.10.046