With the following data set, what is the best way to interpolate the data for each time.
Time X Y 0 10 15 ... ... 24 28 17 ... ... 49 9 14
With the following data set, what is the best way to interpolate the data for each time.
Time X Y 0 10 15 ... ... 24 28 17 ... ... 49 9 14
You can use Newton's divided differences interpolation polynomial which is easy to use and if you add a new point to the set, you don't have to calculate everything again.
So you'll have a table with four columns, $x_i, y_i$ and divided differences where:
$f\left[x_0,x_1,\dots, x_n\right]=\dfrac{f\left[x_0,x_1,\dots, x_{n-1}\right]-f\left[x_1,\dots, x_n\right]}{x_0-x_n}$
Then, for example, you have:
$x_0=10, y_0=15, x_1=28,y_1=17$: $f[x_0,x_1]=\dfrac{y_0-y_1}{x_0-x_1}=\dfrac{15-17}{10-28}=0.11$
$f[x_1,x_2]=\dfrac{17-14}{28-9}=0.15$
$f[x_0,x_1,x_2]=\dfrac{0.11-0.15}{10-9}$
Thus, the interpolating polynomial is:
$p(x)=f_0+(x-x_0)f[x+0,x_1]+\dots+(x-x)\dots(x-x_{n-1})f[x+0,\dots,x_n]$
And it's easy to take it from here.