Article http://dx.doi.org/10.26855/ijsds.2025.12.001

Predicting a Random Determinant with I.I.D. Neg-ative Binomial Variates

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Shashi Kant Agrawal1, Pinky Pandey2, Soubhik Chakraborty3,*

1University Department of Mathematics, Ranchi University, Ranchi 834008, India.

2Department of Mathematics, Nirmala College, Ranchi University, Ranchi 834002, India.

3Department of Mathematics, Birla Institute of Technology Mesra, Ranchi 835215, India.

*Corresponding author: Soubhik Chakraborty

Published: August 1,2025

Abstract

This paper gives a probabilistic analysis of a determinant D of order 2 and 3 in which the elements are i.i.d. Negative Binomial variates. Using Chebyshev’s ine-quality, fiducial limits (a type of statistical range used to estimate the uncertainty around a measured value) of D are obtained for order 2 and 3. The results may be compared with those obtained for other standard probability distributions. We are motivated to work in this problem considering the following applications: (1) Pre-dicting the area of a triangle whose vertices are random variables. (2) In solving optimization problems where the coefficients in the objective function or the con-straints are random variables. (3) Predicting the product of vectors (Cross Product) whose elements are random variables. (4) Predicting the equation of a plane con-taining two straight lines (in 3D) whose coefficients are random variables. (5) Pre-dicting the Eigen values and Eigen vectors for random square matrices. (6) Pre-dicting the solution of system of simultaneous linear equations, whose coefficients are random variables, using Cramer's rule.

Keywords

Random Determinant; Negative Binomial Distribution; Chebyshev's inequality Mathematics Subject Classification: 62P99

References

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How to cite this paper

Predicting a Random Determinant with I.I.D. Negative Binomial Variates

How to cite this paper: Shashi Kant Agrawal, Pinky Pandey, Soubhik Chakraborty. (2025) Predicting a Random Determinant with I.I.D. Negative Binomial Variates. International Journal of Statistics and Data Science, 1(1), 1-6.

DOI: http://dx.doi.org/10.26855/ijsds.2025.12.001