Problem $2/$ Mat labGrader $(20$ points$)($Core Course Outcome $4)$

Devlop Problem $2/$ Mat labGrader $(20$ points$)($Core Course Outcome $4)$

Develop a Matlab function myFitExam that finds the best fit of the function

$p(t)=\frac{1}{a{t}^3+b{t}^2+ct+d}$

to a given set of data points $(t_i,p_i)$ using regression.

The function input shall be

$t$ : column vector of data values $t$

p: column vector of data values $p$

The function output shall be

a: scalar containing the best fit coefficient $a$

b: scalar containing the best fit coefficient $b$

c: scalar containing the best fit coefficient $c$

$d$ : scalar containing the best fit coefficient $d$

In the function use only functions developed in this class in modules $1-4.$ You do not need to provide these functions

in your submission. They will be provided when assessing your function after the deadline.a Matlab function myFitExam that finds the best fit of the function

$p(t)=\frac{1}{a{t}^3+b{t}^2+ct+d}$

to a given set of data points $(t_i,p_i)$ using regression.

The function input shall be

$t$ : column vector of data values $t$

$p$ : column vector of data values $p$

The function output shall be

a: scalar containing the best fit coefficient $a$

b: scalar containing the best fit coefficient $b$

c: scalar containing the best fit coefficient $c$

$d$ : scalar containing the best fit coefficient $d$

In the function use only functions developed in this class in modules $1-4.$ You do not need to provide these functions

in your submission. They will be provided when assessing your function after the deadline.

Some of the things you can use are linear least square regression and name the function myLinReg and also you can use myGaussJordan for gauss jordan elimination to solve the equations. Do not use in built matlab function