Содержание
I-XII — Part I Limit Theorems, Rates of Convergence, and Related Topics (Independent Case) — ORDER OF NORMAL APPROXIMATION FOR RANK TEST STATISTICS DISTRIBUTION — CONVERGENCE AND REMAINDER TERMS IN LINEAR RANK STATISTICS — INVARIANCE PRINCIPLES FOR RANK STATISTICS FOR TESTING INDEPENDENCE — ON THE DEGENERATION OF THE VARIANCE IN THE ASYMPTOTIC NORMALITY OF SIGNED RANK STATISTICS — ON THE ORDER OF MAGNITUDE OF CUMULANTS OF VON MISES FUNCTIONALS AND RELATED STATISTICS — ON BERRY-ESSEEN RATES, A LAW OF THE ITERATED LOGARITHM AND AN INVARIANCE PRINCIPLE FOR THE PROPORTION OF THE SAMPLE BELOW THE SAMPLE MEAN — CRAMÉR TYPE LARGE DEVIATIONS FOR GENERALIZED RANK STATISTICS — ON THE RATE OF CONVERGENCE IN THE CENTRAL LIMIT THEOREM FOR SIGNED RANK STATISTICS — A SHARPENING OF THE REMAINDER TERM IN THE HIGHER-DIMENSIONAL CENTRAL LIMIT THEOREM FOR MULTILINEAR RANK STATISTICS — THE ORDER OF NORMAL APPROXIMATION FOR SIGNED LINEAR RANK STATISTICS — CENTRAL LIMIT THEOREM FOR PERTURBED EMPIRICAL DISTRIBUTION FUNCTIONS EVALUATED AT A RANDOM POINT — LIMIT THEOREMS FOR RANDOM CENTRAL ORDER STATISTICS — ASYMPTOTIC EXPANSIONS FOR SUMS OF NONIDENTICALLY DISTRIBUTED BERNOULLI RANDOM VARIABLES — ON THE RATE OF CONVERGENCE IN NORMAL APPROXIMATION AND LARGE DEVIATION PROBABILITIES FOR A CLASS OF STATISTICS — ON HILBERT-SPACE-VALUED U-STATISTICS — ON THE CENTRAL LIMIT THEOREM IN HILBERT SPACE WITH APPLICATION TO U-STATISTICS — ASYMPTOTIC EXPANSIONS IN STATISTICS: A REVIEW OF METHODS AND APPLICATIONS — NORMAL APPROXIMATION OF U-STATISTICS IN HILBERT SPACE — Part II Limit Theorems (Dependent Case) — EMPIRICAL DISTRIBUTION FUNCTIONS AND FUNCTIONS OF ORDER STATISTICS FOR MIXING RANDOM VARIABLES — AN INVARIANCE PRINCIPLE FOR PROCESSES INDEXED BY TWO PARAMETERS AND SOME STATISTICAL APPLICATIONS — LIMITING BEHAVIOR OF U-STATISTICS, V-STATISTICS, AND ONE SAMPLE RANK ORDER STATISTICS FOR NONSTATIONARY ABSOLUTELY REGULAR PROCESSES — WEAK INVARIANCE OF GENERALIZED U-STATISTICS FOR NONSTATIONARY ABSOLUTELY REGULAR PROCESSES — THE SPACE D?k AND WEAK CONVERGENCE FOR THE RECTANGLE-INDEXED PROCESSES UNDER MIXING — WEAK INVARIANCE OF THE MULTIDIMENSIONAL RANK STATISTIC FOR NONSTATIONARY ABSOLUTELY REGULAR PROCESSES — WEAK CONVERGENCE OF THE SIMPLE LINEAR RANK STATISTIC UNDER MIXING CONDITIONS IN THE NONSTATIONARY CASE — WEAK CONVERGENCE OF WEIGHTED EMPIRICAL U-STATISTICS PROCESSES FOR DEPENDENT RANDOM VARIABLES — LAW OF THE ITERATED LOGARITHM FOR PERTURBED EMPIRICAL DISTRIBUTION FUNCTIONS EVALUATED AT A RANDOM POINT FOR NONSTATIONARY RANDOM VARIABLES — VALID EDGEWORTH EXPANSIONS OF M-ESTIMATORS IN REGRESSION MODELS WITH WEAKLY DEPENDENT RESIDUALS — CONDITIONAL U-STATISTICS FOR DEPENDENT RANDOM VARIABLES — WEAK CONVERGENCE OF SEQUENCES OF FIRST PASSAGE PROCESSES AND APPLICATIONS — CONDITIONAL EMPIRICAL PROCESSES DEFINED BY NONSTATIONARY ABSOLUTELY REGULAR SEQUENCES — Part III Extreme Value Theory — A STRONG INVARIANCE PRINCIPLE CONCERNING THE J-UPPER ORDER STATISTICS FOR STATIONARY m-DEPENDENT SEQUENCES — A STRONG INVARIANCE PRINCIPLE CONCERNING THE J-UPPER ORDER STATISTICS FOR STATIONARY GAUSSIAN SEQUENCES — EXTREMES OF MARKOV SEQUENCES — RECORDS AND 2-BLOCK RECORDS OF 1-DEPENDENT STATIONARY SEQUENCES UNDER LOCAL DEPENDENCE — Part IV Appendices A, ? and C — Appendix A Volume 1 Nonparametric Methods in Statistics and Related Topics — Appendix ? Volume 3 Time Series, Fuzzy Analysis and Miscellaneous Topics — Appendix C The Publications of Madan Lal Puri