Dirk De Becker wrote: > * Determine the range of the spectrum to be used -> For this, I should > be able to calculate the regression coefficients
You can get the regression coefficients from a PLSR/PCR with the coef() function. See ?coef.mvr However, using the regression coefficients alone for selecting variables/regions, can be 'dangerous' because the variables are highly correlated. One alternative is 'variable importance' measures, e.g. VIP (variable importance in projections) as described in Chong, Il-Gyo & Jun, Chi-Hyuck, 2005, Performance of some variable selection methods when multicollinearity is present, Chemometrics and Intelligent Laboratory Systems 78, 103--112. A crude implementation of VIP can be found in http://mevik.net/work/software/pls.html Another alternative is to use jackknife-estimated uncertainties of the regression coefficients in significance tests. (I don't have any reference or implementation, sorry. :-) The correlation loadings can also give valuable information about which variables that might be important for the regression. See ?corrplot in the pls package. -- Bjørn-Helge Mevik ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
