for matlab

The growth rate of a tree is predicted by G $=$ ln$1/$m$^2+$ b$/$m $+$c$)$ where m is the age of the tree, G is the growth, and a$,$ b and c are constants. A scientist performed an experiment and measured the following data points: m$,,=\{2,5,10,15,20,25,30,35,40\}$ months

and Gexp $=\{5\mathrm{.}7,41.,3\mathrm{.}3,2\mathrm{.}5,2\mathrm{.}1,2\mathrm{.}2,1\mathrm{.}7,1\mathrm{.}6,1\mathrm{.}3\}$ centimeters. Write a function called PlantGrowth to calculate the coefficients a$,$ b and

ce by using regression given experimental datasets mexp and Gexp, and estimate the growth of the plant at a given month.

Restrictions: The function PlantGrowth must use polyfit. Hint: The dataset should be linearized before performing a polynomial fit.

Ex:

m $=[2510152025303540]$; G $=[5\mathrm{.}74\mathrm{.}13\mathrm{.}32\mathrm{.}52\mathrm{.}12\mathrm{.}21\mathrm{.}71\mathrm{.}61\mathrm{.}3]$; $[$growth$]=$ FitPlant$($m$,$ G$,50)$

produces

growth $=$

$1\mathrm{.}3712$

Write a function so that FitPlant$($m$,$ G$,100)$ returns growth $=0\mathrm{.}9181.$

function $[$growth$]=$ FitPlant$($m$,$ G$,$ month$)$

$\%$ Your code goes here

end

code to call function

m $=[2510152025303540]$;

G $=[5\mathrm{.}74\mathrm{.}13\mathrm{.}32\mathrm{.}52\mathrm{.}12\mathrm{.}21\mathrm{.}71\mathrm{.}61\mathrm{.}3]$;

$[$growth$]=$ FitPlant$($m$,$ G$,100)$