QuadRoot

Application of QuadRoot package for finding the roots of a quadratic equation

Introduction

In mathematics, the roots of a quadratic equation are the values of the variable (usually denoted as “x”) that satisfy the equation and make it equal to zero. The general form of a quadratic equation is:

ax^2 + bx + c = 0

where “a,” “b,” and “c” are constants, and “a” is not equal to zero (a ≠ 0). To find the roots of a quadratic equation, you can use the quadratic formula: x = (-b ± √(b² - 4ac)) / (2a)

The symbol “±” indicates that there are usually two roots, one with a plus sign and one with a minus sign, giving you two possible solutions for “x.” These are called the “root” or “zero” of the quadratic equation.

The expression inside the square root, “b² - 4ac,” is called the discriminant. Depending on its value, you can determine the nature of the roots:

If the discriminant (b² - 4ac) is positive, you have two distinct real roots. If the discriminant is zero, you have one real root, which is often referred to as a “double root” or “repeated root.” If the discriminant is negative, you have two complex roots, which are conjugate pairs with real and imaginary parts. So, to find the roots of a given quadratic equation, you can use the quadratic formula and plug in the values of “a,” “b,” and “c” from your specific equation.

Function in the R package

QuadRoot- The Quadroot function helps the user to find simple quadratic roots from any quadratic equation.

Background

A quadratic issue is one in which a variable is multiplied by itself, a process known as squaring in mathematics. The packages was developed using the Sridharacharya formula. It is used to solve the Sridharacharya equation. The Sridharacharya equation is given by ax2 + bx + c = 0, where a, b, c are real numbers and a ≠ 0. The solution of the Sridharacharya equation is given by the Sridharacharya formula which is x = (-b ± √(b2 - 4ac)) / 2a.

##Example how the package works
library(QuadRoot)
#the roots of the quadratic equation 2x² + 5x - 3 = 0
#Coefficient vector generation
dataset <- c(2,5,-3)

#Application of EMDANN model
QuadRoot(dataset)
#> [1] "The two x-intercepts for the quadratic equation are 0.5000 and -3.0000."