Amit N. Kumar

most citedBounds on Negative Binomial Approximation to Call Function

1 citations · 1 across the 2 of their papers we have counts for

collaborators

Showing math.PRShow all

4 papers · 1 filter

math.PR2022★ 1 cited

Binomial Approximation to Locally Dependent CDO

Amit N. Kumar, P. Vellaisamy

In this paper, we develop Stein's method for binomial approximation using the stop-loss metric that allows one to obtain a bound on the error term between the expectation of call f…

math.PR2021★ 1 cited

Bounds on Negative Binomial Approximation to Call Function

Amit N. Kumar

In this paper, we develop Stein's method for negative binomial distribution using call function defined by $f_{z} (k) = (k - z)^{+} = max {k - z, 0}$ , for $k \geq 0$ and $z \geq 0$ . We obtain err…

math.PR2020

Approximations to Weighted Sums of Random Variables

Amit N. Kumar

In this paper, we obtain error bound for binomial and negative binomial approximations to weighted sums of locally dependent random variables, using Stein's method. We also discuss…

math.PR2020

Approximations Related to the Sums of $m$ -dependent Random Variables

Amit N. Kumar, Neelesh S. Upadhye, P. Vellaisamy

In this paper, we consider the sums of non-negative integer valued $m$ -dependent random variables, and its approximation to the power series distribution. We first discuss some rel…

Binomial Approximation to Locally Dependent CDO

Bounds on Negative Binomial Approximation to Call Function

Approximations to Weighted Sums of Random Variables

Approximations Related to the Sums of m-dependent Random Variables

Approximations Related to the Sums of $m$ -dependent Random Variables