Hey all! I am working on my master thesis and I am desperate with my model. It looks as following:
Y(t) = β1*X1(t) + β2*X2(t) + δ*(β1*((1+c)/(δ+c))+β2)*IE(t) - β2*α*((1+c)/(δ+c))*(δ+g)* IE(t-1) note: c and g is a constant value The problem I encounter is that between IE(t) and IE(t-1) there is strong linear correlation (autocorrelation). How can I solve this problem? Of utterly importance is to have finally a significant coefficient δ and α which is than used for a consecutive model. However, I get either no significant values for δ and α, or for one of the two some unrealistic values. Is there an option to combine both in using some non-linear time lagged model, time series or plugged in autoregression? A following up question would be how to place penalties for this model. I would like to restrict values for δ and α between 0 and 0.5 and add penalties when they come closer to the boundaries. I really need some help. Because I am stuck with it for the last two weeks and don't know how to go about it. Thanks for the support Cheers, Bob -- View this message in context: http://r.789695.n4.nabble.com/Autocorrelation-in-non-linear-regression-model-tp3385647p3385647.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.