Uncertainty for regressed parameters using nlinfit considering the uncertainty of data

Hello everyone,

I have some experimental data and I used a non-linear model to describe the data. The model has two independent variables (z-position and t-time) and one dependent variable . So, my experimental data is defined as , where each pair of value (z, t) leads to a unique value of . The model can be described as:

where is an empirical parameter, is the last time instance, and function f is defined by:

H, b are constants for a given problem, and I considered only the first 100 terms in n.

I applied the nlinfit algorithm, and I get the three estimated parameters of the model ( and D). Also, from CovB matrix I get the standard deviation (relative uncertainty) of these parameters.

Now, I would like to consider the uncertainty of my experimental data (which is known) and calculate its contribution in the total uncertainty of the parameters. How could I do this?

Thanks in advance.