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Stability in Quasineutral Plasmas with Thermalized Electrons. [PDF]
Ann PDEGriffin-Pickering M, Iacobelli M.
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Stability and Hopf bifurcation analysis of a fractional-order Filippov prey-predator model with prey refuge and fear effects. [PDF]
Sci RepNadeem M +3 more
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Evolution of a trait distributed over a large fragmented population: propagation of chaos meets adaptive dynamics. [PDF]
J Math BiolLambert A +3 more
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Finite-Resolution Information from Collision Statistics. [PDF]
Entropy (Basel)Gates AJ.
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Phylogenetic Network Models as Graphical Models. [PDF]
Bull Math BiolSullivant S.
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On a Local Limit Theorem for Lattice Distributions
Theory of Probability & Its Applications, 1957Let sequence (1) of independent random variables assuming only integral values satisfy conditions (A) and (B). The following proposition is proved:In order for correlation (2) to hold true for a sequence differing from (1) only by a finite number of terms, it is necessary and sufficient for (3) to be satisfied.
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A LOCAL LIMIT THEOREM FOR CONTINUED FRACTIONS
Stochastics and Dynamics, 2010It is shown that functionals of digits in continued fraction expansion satisfy either the DeMoivre–Gnedenko or the Shepp–Stone limit theorems if and only if their marginals are in the domain of attraction of the normal law.
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APERIODICITY OF COCYCLES AND CONDITIONAL LOCAL LIMIT THEOREMS
Stochastics and Dynamics, 2004We establish conditions for aperiodicity of cocycles (in the sense of [12]), obtaining, via a study of perturbations of transfer operators, conditional local limit theorems and exactness of skew-products. Our results apply to a large class of Markov and non-Markov interval maps, including beta transformations.
Zweimueller, R +3 more
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1975
We consider a sequence of independent random variables {X n ; n = 1, 2,…). We shall suppose for simplicity that these variables have a common distribution with zero mean and nonzero variance σ2 < ∞. If \({S_n} = \sum\limits_{j = 1}^n {{X_j}}\) and \({F_n}\left( x \right) = P\left( {{S_n} < x\sigma \sqrt n } \right)\), the assumptions imply that F n (x)
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We consider a sequence of independent random variables {X n ; n = 1, 2,…). We shall suppose for simplicity that these variables have a common distribution with zero mean and nonzero variance σ2 < ∞. If \({S_n} = \sum\limits_{j = 1}^n {{X_j}}\) and \({F_n}\left( x \right) = P\left( {{S_n} < x\sigma \sqrt n } \right)\), the assumptions imply that F n (x)
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Local Limit Theorems for Compound Discrete Distributions
Theory of Probability & Its Applications, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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