Creating the 5 indicator variables will be easy if you post your code and sample data. This may also allow people to help with the first problem you were having.
Tom 2010/5/14 William Simpson <william.a.simp...@gmail.com>: > [posted this at 9:25 and still hasn't appeared on the list at 13:26] > > > I have the following set-up. > > 6 values of a continuous variable (let's say light intensity) are > presented to a system. > The input is presented as a random series of blocks lasting (say) 5 sec each. > ---- > ---- > ---- etc > ---- > time -> > > The output is measured and sampled at say 10 samples/sec. Please > ignore the fact that this is a time series and don't suggest things > like ar() and arima(). I have looked at the autocorrelation function > of the output and it is an amazing spike at a lag of zero and zilch > elsewhere. > > Call the input x and the output y. > > I can find the relationship between x and y by > fit<-lm(y~x) > coef(fit) tells me the line that best fits x vs y (as shown in the > plot of the 6 values of x vs the mean values of y at those values). > > ****Question: > Suppose that the system is nonlinear such that the response to the > sequence 0,2 is not the same as the response to 2, 0 -- it is not just > a change of the response by the same amount. Or nonlinear in other > weird ways (I don't just mean simple things like y~x^2). > > I am thinking that a way to characterise this might be to pretend that > x is not a continuous variable and to represent it with 5 indicator > variables. And then interactions between them would tell me about > nonlinear effects? > e.g. > lm(y~ d1 + d2 + d3 + d4 + d5 + d1*d2) etc > Does this make any sense? If so, please suggest a good way to go about > this; how to set up the dummy variables and how to interpret the > results. > > Ideally, the same lm() fit would tell me about the linear effect y~x > and the nonlinearities. Both sorts of effect will co-exist. > > Thanks very much for any help! > > Bill > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
