How to change r code to Matlab

I have a code for linear fit in r that I want to do in matlab. I have converted up to this point and then not exactly sure how to do the rest.

This is a simple linear regression in r that uses the lm function that is "linearmodel" to create a simple linear regression model

fit=lm(dependant variable ~ indepentand varible)

the reture should be the coefficients of the model

Is there a way to do this in matlab

fit <- lm((log(obs$O2)-log(0.247))~ obs$depth + 0)

[dpb]

My R syntax is too rusty...what's the wanted model in something can decipher?

[Walter Roberson]

depth to be fit to O2^0.247 ??

Answer 1

[Bjorn Gustavsson]

Well if it is as simple as a fit of a line to data you can always use polyfit, or lscov if you have known uncertainties in your measurements. Those functions is what I typically start with for fitting low-order polynomials to data. Those would give you polynomial coefficients (polyfit) and whatever coefficients you'd fit for with the lscov function (it allows you to build your fitting matrix A with whatever you like not just values of powers of independent variable...)

HTH