# Formula for finding variables by regression

I'm trying to fit data to the following formula:

$$y = a + b x + c/(Sqrt[x]+d)$$

$y=a + b x$ can be fitted easily with linear regression, but I'm lost when it comes to anything more complicated.

Can anyone explain to me how I can build regression formulas for more complicated equations?

The model being $$y=a+bx+\frac c {\sqrt x +d}$$ it is nonlinear with respect to the parameters (because of $d$) and adjusting coefficients $a,b,c,d$ will require nonlinear regression and this will also require some reasonables estimates of the parameters for starting it.
What you could notice is that, for a fixed value of $d$, the model is linear. For a given $d$, define $z_i=\frac 1 {\sqrt x_i +d}$ which makes the model to be $$y=a+bx+cz$$So, for this value of $d$, you can compute $a,b,c$ using multilinear regression. So, consider that $d$ is fixed at a given value and compute $$SSQ(d)=\sum_{i=1}^n\Big(a+bx_i+cz_i-y_i\Big)^2$$ Plot the function and locate more or less a minimum. At that point, you are ready for the nonlinear regression.