> On Jul 13, 2017, at 10:43 AM, Bert Gunter <bgunter.4...@gmail.com> wrote: > > poly(NIR, degree = 2) will work if NIR is a matrix, not a data.frame. > The degree argument apparently *must* be explicitly named if NIR is > not a numeric vector. AFAICS, this is unclear or unstated in ?poly.
I still get the same error with: library(pld) data(gasoline) gasTrain <- gasoline[1:50,] gas1 <- plsr(octane ~ poly(as.matrix(NIR), 2), ncomp = 10, data = gasTrain, validation = "LOO") Error in rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : invalid 'times' value > gas1 <- plsr(octane ~ poly(as.matrix(gasTrain$NIR), degree=2), ncomp = 10, > data = gasTrain, validation = "CV") Error in rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : invalid 'times' value > str(as.matrix(gasTrain$NIR)) AsIs [1:50, 1:401] -0.0502 -0.0442 -0.0469 -0.0467 -0.0509 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:50] "1" "2" "3" "4" ... ..$ : chr [1:401] "900 nm" "902 nm" "904 nm" "906 nm" ... So tried to strip the RHS down to a "simple" matrix > gas1 <- plsr(octane ~ poly(matrix(gasTrain$NIR, nrow=nrow(gasTrain$NIR) ), > degree=2), ncomp = 10, data = gasTrain, validation = "CV") Error in rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : invalid 'times' value I guess it reflects my lack of understanding of poly (which parallels my lack of understanding of PLS.) -- David. > > > -- Bert > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along > and sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Thu, Jul 13, 2017 at 10:15 AM, David Winsemius > <dwinsem...@comcast.net> wrote: >> >>> On Jul 12, 2017, at 6:58 PM, Ng, Kelvin Sai-cheong <ks...@connect.hku.hk> >>> wrote: >>> >>> 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 predict.octane[i] = a[0] * NIR[0,i] + a[1] * >>> NIR[1,i] + ... >>> I want to fit the data with: >>> predict.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. >> >> I did not see any terms in the model that I would have called interaction >> terms. I'm seeing a desire for a polynomial function in NIR. For that >> purpose, one might see if you get satisfactory results with: >> >> gas1 <- plsr(octane ~NIR + I(NIR^2), ncomp = 10, data = gasTrain, validation >> = "LOO") >> gas1 >> >> I first tried using poly(NIR, 2) on the RHS and it threw an error, which >> raises concerns in my mind that this may not be a proper model. I have no >> experience with the use of plsr or its underlying theory, so the fact that >> this is not throwing an error is no guarantee of validity. Using this >> construction in ordinary least squares regression has dangers with >> inferential statistics because of the correlation of the linear and squared >> terms as well as likely violation of homoscedasticity. >> >> -- >> David. >> >> >>> >>> 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. >> >> David Winsemius >> Alameda, CA, USA >> >> ______________________________________________ >> 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. David Winsemius Alameda, CA, USA ______________________________________________ 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.
