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Negatively associated random variable
Complete convergence
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Weighted sums
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Extended negatively dependent
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Complete consistency
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Complete moment convergence
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Negatively dependent
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Almost sure convergence
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Almost sure limit theorem
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EV regression model
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Glivenko–Cantelli lemma
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I.i.d. random variable
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Kolmogorov-type exponential inequality
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Marcinkiewicz-Zygmund type SLLN
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Marcinkiewicz–Zygmund strong laws of larger numbers
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Martingale difference fields
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Maximal weighted sums
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Mixing dependency
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NA
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Negatively quadrant dependent
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Negatively superadditive-dependent random variables
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Pairwise independent random variables
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Rosenthal type inequality
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Small deviation probabilities
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Strong Approximation
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Strong convergence
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Strong law of large numbers
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Sums of i.i.d. random variables
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Tail Probabilities of Sums of i.i.d Random Variables
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The law of the iterated logarithm
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The rate of approximation
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On the strong convergence for weighted sums of random variables
Sung, Soo
- In:
Statistical Papers
52
(
2011
)
2
,
pp. 447-454
Persistent link: https://www.econbiz.de/10009149824
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