scholarly journals Large Deviation Local Limit Theorems for Ratio Statistics

1988 ◽  
Author(s):  
Narasinga R. Chaganty ◽  
Sanjeev Sabnis
1989 ◽  
Author(s):  
Narasinga R. Chaganty ◽  
Jayaram Sethuraman

1993 ◽  
Vol 21 (3) ◽  
pp. 1671-1690 ◽  
Author(s):  
Narasinga Rao Chaganty ◽  
Jayaram Sethuraman

1986 ◽  
Author(s):  
Narasinga R. Chaganty ◽  
Jayaram Sethuraman

1990 ◽  
Vol 19 (11) ◽  
pp. 4083-4101
Author(s):  
Narasinga Rao Chaganty ◽  
Sanjeev Sabnis

1986 ◽  
Vol 20 (2) ◽  
pp. 190-204 ◽  
Author(s):  
Narasinga R. Chaganty ◽  
J. Sethuraman

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 880
Author(s):  
Igoris Belovas

In this research, we continue studying limit theorems for combinatorial numbers satisfying a class of triangular arrays. Using the general results of Hwang and Bender, we obtain a constructive proof of the central limit theorem, specifying the rate of convergence to the limiting (normal) distribution, as well as a new proof of the local limit theorem for the numbers of the tribonacci triangle.


2020 ◽  
Vol 30 (4) ◽  
pp. 215-241
Author(s):  
Gavriil A. Bakay ◽  
Aleksandr V. Shklyaev

AbstractLet (ξ(i), η(i)) ∈ ℝd+1, 1 ≤ i < ∞, be independent identically distributed random vectors, η(i) be nonnegative random variables, the vector (ξ(1), η(1)) satisfy the Cramer condition. On the base of renewal process, NT = max{k : η(1) + … + η(k) ≤ T} we define the generalized renewal process ZT = $\begin{array}{} \sum_{i=1}^{N_T} \end{array}$ξ(i). Put IΔT(x) = {y ∈ ℝd : xj ≤ yj < xj + ΔT, j = 1, …, d}. We find asymptotic formulas for the probabilities P(ZT ∈ IΔT(x)) as ΔT → 0 and P(ZT = x) in non-lattice and arithmetic cases, respectively, in a wide range of x values, including normal, moderate, and large deviations. The analogous results were obtained for a process with delay in which the distribution of (ξ(1), η(1)) differs from the distribution on the other steps. Using these results, we prove local limit theorems for processes with regeneration and for additive functionals of finite Markov chains, including normal, moderate, and large deviations.


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