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E-raamat: Probability Inequalities

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  • Ilmumisaeg: 30-May-2011
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642052613
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 30-May-2011
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642052613
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Inequality has become an essential tool in many areas of mathematical research, for example in probability and statistics where it is frequently used in the proofs. "Probability Inequalities" covers inequalities related with events, distribution functions, characteristic functions, moments and random variables (elements) and their sum. The book shall serve as a useful tool and reference for scientists in the areas of probability and statistics, and applied mathematics.



Prof. Zhengyan Lin is a fellow of the Institute of Mathematical Statistics and currently a professor at Zhejiang University, Hangzhou, China. He is the prize winner of National Natural Science Award of China in 1997. Prof. Zhidong Bai is a fellow of TWAS and the Institute of Mathematical Statistics; he is a professor at the National University of Singapore and Northeast Normal University, Changchun, China.

Arvustused

From the reviews:

This is a relatively short book of 181 pages organized in 12 chapters with the avowed aim of introducing beginning research workers in probability and statistics to `frequently used inequalities. I would heartily recommend this book to beginning researchers wanting to find `frequently used inequalities and learn some of the standard arguments. (Jon Wellner, SIAM Review, Vol. 54 (2), 2012)

This book contains a large collection of probability inequalities. The authors present most of the results with proofs. The book is useful addition and a valuable source for any researcher in probability and statistics. (B. L. S. Prakasa Rao, Zentralblatt MATH, Vol. 1221, 2011)

Chapter 1 Elementary Inequalities of Probabilities of Events
1(8)
1.1 Inclusion-exclusion Formula
1(1)
1.2 Corollaries of the Inclusion-exclusion Formula
2(1)
1.3 Further Consequences of the Inclusion-exclusion Formula
2(4)
1.4 Inequalities Related to Symmetric Difference
6(1)
1.5 Inequalities Related to Independent Events
6(2)
1.6 Lower Bound for Union (Chung-Erdos)
8(1)
References
8(1)
Chapter 2 Inequalities Related to Commonly Used Distributions
9(14)
2.1 Inequalities Related to the Normal d.f.
9(3)
2.2 Slepian Type Inequalities
12(5)
2.3 Anderson Type Inequalities
17(1)
2.4 Khatri-Sidak Type Inequalities
18(1)
2.5 Corner Probability of Normal Vector
19(1)
2.6 Normal Approximations of Binomial and Poisson Distributions
20(2)
References
22(1)
Chapter 3 Inequalities Related to Characteristic Functions
23(6)
3.1 Inequalities Related Only with c.f.
23(3)
3.2 Inequalities Related to c.f. and d.f.
26(1)
3.3 Normality Approximations of c.f. of Independent Sums
27(1)
References
28(1)
Chapter 4 Estimates of the Difference of Two Distribution Functions
29(8)
4.1 Fourier Transformation
29(4)
4.2 Stein-Chen Method
33(1)
4.3 Stieltjes Transformation
34(2)
References
36(1)
Chapter 5 Probability Inequalities of Random Variables
37(14)
5.1 Inequalities Related to Two r.v.'s
37(2)
5.2 Perturbation Inequality
39(1)
5.3 Symmetrization Inequalities
40(1)
5.4 Levy Inequality
41(1)
5.5 Bickel Inequality
42(2)
5.6 Upper Bounds of Tail Probabilities of Partial Sums
44(1)
5.7 Lower Bounds of Tail Probabilities of Partial Sums
44(1)
5.8 Tail Probabilities for Maximum Partial Sums
45(1)
5.9 Tail Probabilities for Maximum Partial Sums (Continuation)
46(1)
5.10 Reflection Inequality of Tail Probability (Hoffmann-Jørgensen)
47(1)
5.11 Probability of Maximal Increment (Shao)
48(1)
5.12 Mogulskii Minimal Inequality
49(1)
5.13 Wilks Inequality
50(1)
References
50(1)
Chapter 6 Bounds of Probabilities in Terms of Moments
51(16)
6.1 Chebyshev-Markov Type Inequalities
51(1)
6.2 Lower Bounds
52(1)
6.3 Series of Tail Probabilities
53(1)
6.4 Kolmogorov Type Inequalities
54(2)
6.5 Generalization of Kolmogorov Inequality for a Submartingale
56(1)
6.6 Renyi-Hajek Type Inequalities
57(3)
6.7 Chernoff Inequality
60(2)
6.8 Fuk and Nagaev Inequality
62(1)
6.9 Burkholder Inequality
63(2)
6.10 Complete Convergence of Partial Sums
65(1)
References
65(2)
Chapter 7 Exponential Type Estimates of Probabilities
67(17)
7.1 Equivalence of Exponential Estimates
67(1)
7.2 Petrov Exponential Inequalities
68(2)
7.3 Hoeffding Inequality
70(2)
7.4 Bennett Inequality
72(1)
7.5 Bernstein Inequality
73(1)
7.6 Exponential Bounds for Sums of Bounded Variables
74(1)
7.7 Kolmogorov Inequalities
75(4)
7.8 Prokhorov Inequality
79(1)
7.9 Exponential Inequalities by Censoring
80(2)
7.10 Tail Probability of Weighted Sums
82(1)
References
83(1)
Chapter 8 Moment Inequalities Related to One or Two Variables
84(13)
8.1 Moments of Truncation
84(1)
8.2 Exponential Moment of Bounded Variables
84(1)
8.3 Holder Type Inequalities
85(1)
8.4 Jensen Type Inequalities
86(1)
8.5 Dispersion Inequality of Censored Variables
87(1)
8.6 Monotonicity of Moments of Sums
88(1)
8.7 Symmetrization Moment Inequatilies
88(1)
8.8 Kimball Inequality
89(1)
8.9 Exponential Moment of Normal Variable
90(3)
8.10 Inequatilies of Nonnegative Variable
93(1)
8.11 Freedman Inequality
94(1)
8.12 Exponential Moment of Upper Truncated Variables
95(1)
References
96(1)
Chapter 9 Moment Estimates of (Maximum of) Sums of Random Variables
97(33)
9.1 Elementary Inequalities
97(2)
9.2 Minkowski Type Inequalities
99(1)
9.3 The Case 1 ≤ r ≤ 2
100(1)
9.4 The Case r ≥ 2
101(4)
9.5 Jack-knifed Variance
105(1)
9.6 Khintchine Inequality
106(2)
9.7 Marcinkiewicz-Zygmund-Burkholder Type Inequalities
108(3)
9.8 Skorokhod Inequalities
111(1)
9.9 Moments of Weighted Sums
112(1)
9.10 Doob Crossing Inequalities
113(1)
9.11 Moments of Maximal Partial Sums
114(1)
9.12 Doob Inequalities
115(2)
9.13 Equivalence Conditions for Moments
117(6)
9.14 Serfling Inequalities
123(4)
9.15 Average Fill Rate
127(1)
References
128(2)
Chapter 10 Inequalities Related to Mixing Sequences
130(19)
10.1 Covariance Estimates for Mixing Sequences
131(3)
10.2 Tail Probability on α-mixing Sequence
134(1)
10.3 Estimates of 4-th Moment on ρ-mixing Sequence
135(1)
10.4 Estimates of Variances of Increments of ρ-mixing Sequence
136(2)
10.5 Bounds of 2 + δ-th Moments of Increments of ρ-mixing Sequence
138(2)
10.6 Tail Probability on φ-mixing Sequence
140(2)
10.7 Bounds of 2 + δ-th Moment of Increments of φ-mixing Sequence
142(1)
10.8 Exponential Estimates of Probability on φ-mixing Sequence
143(5)
References
148(1)
Chapter 11 Inequalities Related to Associative Variables
149(9)
11.1 Covariance of PQD Varaibles
149(1)
11.2 Probability of Quadrant on PA (NA) Sequence
150(1)
11.3 Estimates of c.f.'s on LPQD (LNQD) Sequence
151(1)
11.4 Maximal Partial Sums of PA Sequence
152(1)
11.5 Variance of Increment of LPQD Sequence
153(1)
11.6 Expectation of Convex Function of Sum of NA Sequence
154(2)
11.7 Marcinkiewicz-Zygmund-Burkholder Inequality for NA Sequence
156(1)
References
157(1)
Chapter 12 Inequalities about Stochastic Processes and Banach Space Valued Random Variables
158(22)
12.1 Probability Estimates of Supremums of a Wiener Process
158(4)
12.2 Probability Estimate of Supremum of a Poisson Process
162(2)
12.3 Fernique Inequality
164(3)
12.4 Borell Inequality
167(1)
12.5 Tail Probability of Gaussian Process
168(1)
12.6 Tail Probability of Randomly Signed Independent Processes
168(2)
12.7 Tail Probability of Adaptive Process
170(2)
12.8 Tail Probability on Submartingale
172(1)
12.9 Tail Probability of Independent Sum in B-Space
173(1)
12.10 Isoperimetric Inequalities
173(1)
12.11 Ehrhard Inequality
174(1)
12.12 Tail Probability of Normal Variable in B-Space
175(1)
12.13 Gaussian Measure on Symmetric Convex Sets
175(1)
12.14 Equivalence of Moments of B-Gaussian Variables
176(1)
12.15 Contraction Principle
176(2)
12.16 Symmetrization Inequalities in B-Space
178(1)
12.17 Decoupling Inequality
178(2)
References 180