STRONG INVARIANCE PRINCIPLES FOR DEPENDENT RANDOM VARIABLES
暂无分享,去创建一个
[1] W. Philipp,et al. Almost sure invariance principles for partial sums of weakly dependent random variables , 1975 .
[2] W. Philipp. Invariance Principles for Independent and Weakly Dependent Random Variables , 1986 .
[3] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .
[4] Hajo Holzmann,et al. Some remarks on the central limit theorem for stationary Markov processes , 2004 .
[5] Wei Biao Wu,et al. LOCAL WHITTLE ESTIMATION OF FRACTIONAL INTEGRATION FOR NONLINEAR PROCESSES , 2007, Econometric Theory.
[6] H. Tong. Non-linear time series. A dynamical system approach , 1990 .
[7] E. Rio. The Functional Law of the Iterated Logarithm for Stationary Strongly Mixing Sequences , 1995 .
[8] C. Newman,et al. Limit theorems for sums of dependent random variables occurring in statistical mechanics , 1978 .
[9] M. Peligrad,et al. A maximal _{}-inequality for stationary sequences and its applications , 2006 .
[10] C. C. Heyde,et al. Invariance Principles for the Law of the Iterated Logarithm for Martingales and Processes with Stationary Increments , 1973 .
[11] W. Stout. Almost sure convergence , 1974 .
[12] The Law of the Iterated Logarithm for Mixing Stochastic Processes , 1969 .
[13] Vitesses de convergence dans la loi forte des grands nombres pour des variables dépendantes , 2004 .
[14] P. Hall,et al. Martingale Limit Theory and its Application. , 1984 .
[15] Ernst Eberlein,et al. On Strong Invariance Principles Under Dependence Assumptions , 1986 .
[16] A note on Strassen’s version of the law of the iterated logarithm , 1973 .
[17] D. McLeish. A Maximal Inequality and Dependent Strong Laws , 1975 .
[18] M. Peligrad,et al. A MAXIMAL Lp-INEQUALITY FOR STATIONARY SEQUENCES AND ITS APPLICATIONS , 2005 .
[19] Volker Strassen,et al. Almost sure behavior of sums of independent random variables and martingales , 1967 .
[20] Ernst Eberlein,et al. Dependence in probability and statistics : a survey of recent results (Oberwolfach, 1985) , 1988 .
[21] R. Serfling,et al. Convergence Properties of $S_n$ Under Moment Restrictions , 1970 .
[22] M. B. Priestley,et al. Non-linear and non-stationary time series analysis , 1990 .
[23] F. Móricz. Moment inequalities and the strong laws of large numbers , 1976 .
[24] P. Major,et al. An approximation of partial sums of independent RV's, and the sample DF. II , 1975 .
[25] D. Volný. Approximating martingales and the central limit theorem for strictly stationary processes , 1993 .
[26] P. Phillips. Unit root log periodogram regression , 2007 .
[27] W. Woyczynski. Asymptotic behavior of martingales in Banach spaces II , 1982 .
[28] J. Dedecker,et al. The conditional central limit theorem in Hilbert spaces , 2003 .
[29] Magda Peligrad,et al. A new maximal inequality and invariance principle for stationary sequences , 2004, math/0406606.
[30] J. Doob. Stochastic processes , 1953 .
[31] W. Stout. The Hartman-Wintner Law of the Iterated Logarithm for Martingales , 1970 .
[32] R. C. Bradley. Approximation theorems for strongly mixing random variables. , 1983 .
[33] M. Kh. Reznik. The Law of the Iterated Logarithm for Some Classes of Stationary Processes , 1968 .
[34] W. Wu,et al. On linear processes with dependent innovations , 2005 .
[35] D. Menchoff,et al. Sur les séries de fonctions orthogonales , 1923 .
[36] Robert M. Kunst,et al. Forecasting High-Frequency Financial Data with the ARFIMA-ARCH Model , 2001 .
[37] V. Strassen. An invariance principle for the law of the iterated logarithm , 1964 .
[38] Wei Biao Wu,et al. Limit theorems for iterated random functions , 2004, Journal of Applied Probability.
[39] Clémentine Prieur,et al. Coupling for τ-Dependent Sequences and Applications , 2004 .
[40] M. Rosenblatt. Central limit theorem for stationary processes , 1972 .
[41] Richard T. Baillie,et al. Analysing inflation by the fractionally integrated ARFIMA–GARCH model , 1996 .
[42] Robert Serfling. Moment Inequalities for the Maximum Cumulative Sum , 1970 .
[43] T. Lai,et al. Limit theorems for sums of dependent random variables , 1980 .
[44] Jérôme Dedecker,et al. On the functional central limit theorem for stationary processes , 2000 .
[45] Joseph P. Romano,et al. Inference for Autocorrelations under Weak Assumptions , 1996 .
[46] N. Tien,et al. On the convergence of weighted sums of martingale differences , 1989 .
[47] W. Philipp,et al. Approximation Thorems for Independent and Weakly Dependent Random Vectors , 1979 .
[48] Carlo Novara,et al. Nonlinear Time Series , 2003 .
[49] Convergence Rates in the Law of Large Numbers for Banach-Valued Dependent Variables , 2008 .
[50] Jérôme Dedecker,et al. A new covariance inequality and applications , 2003 .
[51] E. J. Hannan,et al. The central limit theorem for time series regression , 1979 .
[52] Martingale approximations for sums of stationary processes , 2004, math/0410160.
[53] Michel Loève,et al. Probability Theory I , 1977 .
[54] Zhengyan Lin,et al. Limit Theory for Mixing Dependent Random Variables , 1997 .
[55] Y. Tse,et al. Forecasting the Nikkei spot index with fractional cointegration , 1999 .
[56] Jacques Akonom,et al. Comportement asymptotique du temps d'occupation du processus des sommes partielles , 1993 .
[57] D. McLeish. Invariance principles for dependent variables , 1975 .
[58] Ryozo Yokoyama,et al. On the central limit theorem and law of the iterated logarithm for stationary processes with applications to linear processes , 1995 .
[59] Law of the iterated logarithm for stationary processes , 2006, math/0612747.
[60] Richard C. Bradley,et al. Introduction to strong mixing conditions , 2007 .
[61] P. Doukhan,et al. Weak Dependence: Models and Applications , 2002 .
[62] P. Doukhan,et al. A new weak dependence condition and applications to moment inequalities , 1999 .
[63] N. Bingham. INDEPENDENT AND STATIONARY SEQUENCES OF RANDOM VARIABLES , 1973 .
[64] T. Hsing,et al. On weighted U-statistics for stationary processes , 2004, math/0410157.
[65] Wei Biao Wu,et al. On the Bahadur representation of sample quantiles for dependent sequences , 2005 .
[66] Q. Shao. Almost sure invariance principles for mixing sequences of random variables , 1993 .
[67] L. Horváth,et al. Limit Theorems in Change-Point Analysis , 1997 .
[68] Wei Biao Wu,et al. Inference of trends in time series , 2007 .
[69] M. Woodroofe. A central limit theorem for functions of a Markov chain with applications to shifts , 1992 .
[70] W. Philipp. A Functional Law of the Iterated Logarithm for Empirical Distribution Functions of Weakly Dependent Random Variables , 1977 .
[71] On the central limit theorem and iterated logarithm law for stationary processes , 1975, Bulletin of the Australian Mathematical Society.
[72] Florence Merlevède,et al. Necessary and sufficient conditions for the conditional central limit theorem , 2002 .
[73] J. Elton. A multiplicative ergodic theorem for lipschitz maps , 1990 .
[74] W. Wu,et al. Nonlinear system theory: another look at dependence. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[75] W. Wu,et al. MODERATE DEVIATIONS FOR STATIONARY PROCESSES , 2008 .
[76] Persi Diaconis,et al. Iterated Random Functions , 1999, SIAM Rev..
[77] P. Major,et al. An approximation of partial sums of independent RV'-s, and the sample DF. I , 1975 .