Below. -- Bert Bert Gunter
On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biag...@gmail.com> wrote: > I have two ideas about it. > > 1- > i) Entering variables in quadratic form is done with the command I > (variable ^ 2) - > plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = > "LOO" > You could also use a new variable NIR_sq <- (NIR) ^ 2 > > ii) To insert a square variable, use syntax I (x ^ 2) - it is very > important to insert I before the parentheses. True, but better I believe: see ?poly. e.g. poly(cbind(x1,x2,x3), degree = 2, raw = TRUE) is a full quadratic polynomial in x1,x2,x3 . > > iii) If you want to make the interaction between x and x ^ 2 use the > command ":" -> x: I(x ^ 2) > > iv) For multiple interactions between x and x ^ 2 use the command "*" -> x > *I (x ^ 2) > > i) plsr (octane ~ NIR + NIR_sq, ncomp = 10, data = gasTrain, validation = > "LOO") I (x ^ 2) > ii)p lsr (octane ~ NIR + I(NIR^2), ncomp = 10, data = gasTrain, validation > = "LOO") I (x ^ 2) > iii)p lsr (octane ~ NIR : I(NIR^2), ncomp = 10, data = gasTrain, validation > = "LOO") I (x ^ 2) > iv)p lsr (octane ~ NIR * I(NIR^2), ncomp = 10, data = gasTrain, validation > = "LOO") I (x ^ 2) > > 2 - For your regression, did you plan to use MARS instead of PLS? > > > > > Dear all, >> I am using the pls package of R to perform partial least square on a set of >> multivariate data. Instead of fitting a linear model, I want to fit my >> data with a quadratic function with interaction terms. But I am not sure >> how. I will use an example to illustrate my problem: >> Following the example in the PLS manual: >> ## Read data >> data(gasoline) >> gasTrain <- gasoline[1:50,] >> ## Perform PLS >> gas1 <- plsr(octane ~ NIR, ncomp = 10, data = gasTrain, validation = "LOO") >> where octane ~ NIR is the model that this example is fitting with. >> NIR is a collective of variables, i.e. NIR spectra consists of 401 diffuse >> reflectance measurements from 900 to 1700 nm. >> Instead of fitting with octane[i] = a[0] * NIR[0,i] + a[1] * NIR[1,i] + ... >> I want to fit the data with: >> octane[i] = a[0] * NIR[0,i] + a[1] * NIR[1,i] + ... + >> b[0]*NIR[0,i]*NIR[0,i] + b[1] * NIR[0,i]*NIR[1,i] + ... >> i.e. quadratic with interaction terms. >> But I don't know how to formulate this. >> May I have some help please? >> Thanks, >> Kelvin > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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 -- To UNSUBSCRIBE and more, see 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.
