Develop a Matlab function 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 $d$