Hi, all

I want to approximate a function to a vector `v`

of 99 values so I can evaluate that function over other values. This can be a simple linear interpolation of the 99 values, but I’d fit a polynomial in case other values don’t fit within the range of the 99 values.

Initially, I thought of using `Polynomials.jl`

to apply the function `fromroots`

as shown in the Quick Start examples of the package’s page.

```
using Polynomials
poly = fromroots(v)
poly(1250) # This could be any other number from 0 to 100,000
```

But the resulting polynomial is rife with monomials of powers that go as high as 99. Many of these monomials have `Inf32`

for coefficients. The evaluation step didn’t work. I did not find a way to limit the maximum degree to the polynomial. A degree of 10, for instance, would be just fine.

Then, thanks an example from the Julia Discord, I found a different way I attempt to implement

```
using Polynomials
fit(x,v, 10)
```

Here, `x`

has the same length as `v`

. However, to my surprise, I got the following error message:

```
ERROR: UndefVarError: fit not defined
```

I have the `Distributions.jl`

also in use and I wonder if this is somehow the reason why `fit`

won’t work (`Distributions.jl`

also has a function called fit). I don’t know how to specify the package for a function. In R, I would’ve done `Polynomials::fit`

, but in Julia that’s no kosher. I searched online for a way to specify the package, but given the results I got, I’m sure I am not framing my search correctly.

Lastly, I learned about `ApproxFun.jl`

. The package has a brief section on “Using ApproxFun for “manual” interpolation”, which seemed just what I have been looking for. However, to achieve such manual interpolation, I must pass a function `f`

and a domain to the function `Fun`

. The problem is that I’m looking for a function `f`

so I can’t provide it.

**Does anyone know how I find a polynomial of a degree D to a set of N numbers so I can use the polynomial to be evaluate at other input values?**

```
# This simple example will reproduce the error I'm having using the function fit.
#
using Polynomials
x = 0.01:0.01:0.99
y = (x.^2).*5 - x.*2 .+ 6
fit(x, y, 10)
```