Results 11 to 20 of about 440,858 (262)
Upper-bound estimates for weighted sums satisfying Cramer’s condition
Lietuvos Matematikos Rinkinys, 2023 Let S = ω1S1 + ω2S2 + ⋯ + ωNSN. Here Sj is the sum of identically distributed random variables and ωj > 0 denotes weight. We consider the case, when Sj is the sum of independent random variables satisfying Cramer’s condition.
Vydas Čekanavičius, Aistė Elijio
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Normal approximation for sum of random number of summands
Lietuvos Matematikos Rinkinys, 2021 Normal aproximationof sum Zt =ΣNti=1Xi of i.i.d. random variables (r.v.) Xi , i = 1, 2, . . . with mean EXi = μ and variance DXi = σ2 > 0 is analyzed taking into consideration large deviations.
Leonas Saulis, Dovilė Deltuvienė
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Polynomial Representations of High-Dimensional Observations of Random Processes
Mathematics, 2021 The paper investigates the problem of performing a correlation analysis when the number of observations is large. In such a case, it is often necessary to combine random observations to achieve dimensionality reduction of the problem.
Pavel Loskot
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Nonparametric estimation in random sum models
Statistica, 2013 Let X1,X2,…,XN be independent, identically distributed, non-negative, integervalued random variables and let N be a non-negative, integer-valued random variable independent of X1,X2,…,XN .
Hassan S. Bakouch, Thomas A. Severini
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Randomly stopped sums with exponential-type distributions
Nonlinear Analysis, 2017 Assume that {ξ1, ξ2, …} are independent and possibly nonidentically distributed random variables. Suppose that η is a nonnegative, nondegenerate at zero and integer-valued random variable, which is independent of {ξ1, ξ2, …}.
Svetlana Danilenko +2 more
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Sum of Fisher-Snedecor
IEEE Open Journal of the Communications Society, 2020 The statistical characterization of a sum of random variables (RVs) is useful for investigating the performance of wireless communication systems.
Hongyang Du +3 more
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MethodsX, 2021 In probability theory and statistics, the probability distribution of the sum of two or more independent and identically distributed (i.i.d.) random variables is the convolution of their individual distributions.
Arne Johannssen +2 more
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Asymptotics for Weighted Random Sums [PDF]
Advances in Applied Probability, 2012 Let {Xi} be a sequence of independent, identically distributed random variables with an intermediate regularly varying right tail F̄. Let (N, C1, C2,…) be a nonnegative random vector independent of the {Xi} with N∈ℕ∪ {∞}. We study the weighted random sum SN=∑{i=1}NCiXi, and its maximum, MN=sup{1≤kN+1∑i=1kCiXi.
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Electronic Journal of Probability, 2011 Let $T$ be a tree with induced partial order $\preceq$. We investigate centered Gaussian processes $X=(X_t)_{t\in T}$ represented as $$ X_t= (t)\sum_{v \preceq t} (v) _v $$ for given weight functions $ $ and $ $ on $T$ and with $( _v)_{v\in T}$ i.i.d. standard normal.
Lifshits, Mikhail, Linde, Werner
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Random convolution of O-exponential distributions
Nonlinear Analysis, 2015 Assume that ξ1, ξ2, ... are independent and identically distributed non-negative random variables having the O-exponential distribution. Suppose that η is a nonnegative non-degenerate at zero integer-valued random variable independent of ξ1, ξ2, ... . In
Svetlana Danilenko, Jonas Šiaulys
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