Results 261 to 270 of about 7,858,530 (320)

Correlations in Uniform Spanning Trees: a Fermionic Approach. [PDF]

J Stat Phys
Rapoport A.
europepmc   +1 more source

Adaptive Neural Control for Constrained Biomimetic Rehabilitation Robots Using a Novel High-Order Integral Barrier Function. [PDF]

Biomimetics (Basel)
Zhang T, Zhang J, Yan P.
europepmc   +1 more source

Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition. [PDF]

Bioinformatics
Zhou T, Mathews DH, Huang L.
europepmc   +1 more source

Density Functional Theory and Information-Theoretic Diagnostics of Quantum Phase Transitions. [PDF]

Entropy (Basel)
Romera E, Nagy Á.
europepmc   +1 more source

On regular variation and local limit theorems

, 1967
W. Feller
semanticscholar   +3 more sources

A Local Limit Theorem for Associated Sequences

Annals of Probability, 1985
A local central limit theorem of the type due to \textit{L. A. Shepp} [Ann. Math. Stat. 35, 419-423 (1964; Zbl 0146.391)] is proved for certain stationary sequences of associated random variables.
exaly   +4 more sources

Some of the next articles are maybe not open access.

Related searches:

Local Limit Theorems for Densities in Orlicz Spaces

Journal of Mathematical Sciences, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
S. G. Bobkov
semanticscholar   +3 more sources

Central limit theorems for local network statistics

Biometrika, 2020
Subgraph counts, in particular the number of occurrences of small shapes such as triangles, characterize properties of random networks. As a result, they have seen wide use as network summary statistics. Subgraphs are typically counted globally, making
P. Maugis
semanticscholar   +1 more source

Local Limit Theorems for Large Deviations

Theory of Probability & Its Applications, 1957
Let $(X_j ),j = 1,2, \cdots $, be a sequence of independent random variables with the distribution functions $V_j (x)$. We assume the existence of ${\bf D}X_j = \sigma _j^2 ,s_n^2 = \sum\nolimits_{j = 1}^n {\sigma _j^2 } ,{\bf E}X_j = 0,j = 1,2, \cdots $. We put \[ Z_n = \sum\limits_{j = 1}^n X_j /s_n .
openaire   +3 more sources