I'd appreciate some direction here. I have a model for a system with two independant variables (i1,i2) and one dependant variable (d). I have experimental data recorded at multiple levels of the dependant variable (x). I need to work out the values for the independant variables that best fit the experimental data recorded for all the dependant variables. I assume I'm going to need the glm() function but I'd really appreciate some pointers in how to actually do this. Do I need to calculate the fits for a range of values of i1 and i2 for each value of d and then look to see what values of i1 and i2 give the best fit over all the experimental data or is there a way of doing this automatically? Please feel free to point me at other reading sources. Many thanks Tom