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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. iii) If you want to

Below. -- Bert Bert Gunter On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at 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

> On Jul 13, 2017, at 7:43 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > Below. > > -- Bert > Bert Gunter > > > > On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: >> I have two ideas about it. >> >> 1- >> i) Entering variables in quadratic form is done with the command I >>

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. -- 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

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

?? If I haven't misunderstood, they are completely different! 1) NIR must be a matrix, or poly(NIR,...) will fail. 2) Due to the previously identified bug in poly, degree must be explicitly given as poly(NIR, degree =2,raw = TRUE). Now consider the following example: > df <-matrix(runif(60),ncol=3) > y <- runif(20) > mdl1 <-lm(y~df*I(df^2)) > mdl2

Hello, I build FireFox-46.0.1 source with llvm to test interprocedural register allocation. The build was successful with out any runtime faliures, here are few stats: Measure W/O IPRA WITH IPRA ======= ======== ========= Total Build Time 76 mins 82.3 mins 8% increment Octane v2.0 JS Benchmark Score (higher is better) 18675.69 19665.16 5% improvement Kraken JS Benchmark time (lower is better)

On Mon, Jun 20, 2016 at 10:06 PM, Davide Italiano <davide at freebsd.org> wrote: > On Sun, Jun 19, 2016 at 11:41 AM, vivek pandya via llvm-dev > <llvm-dev at lists.llvm.org> wrote: > > Hello, > > > > I build FireFox-46.0.1 source with llvm to test interprocedural register > > allocation. > > The build was successful with out any runtime faliures,

> On Jul 13, 2017, at 10:43 AM, Bert Gunter <bgunter.4567 at 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 <-

Hello all useRs, I am tring make a simple surface plot ( 2 by 2 terms of a MARS model (with earth package) but I get the follow error message: > plotmo( mars ) Error: bad index (missing column in x?) I don't no how to workround this... :-( I thanks in advanced by some help! Thanks. Cleber ############### > > ### example code: > library( earth ) > data( gasoline,

Hi, I enabled password encryption and NT clients were able to connect. However, Windows 95 users were not able to connect any more unless they use smbpassword to reset the password (it's not an acceptable solution for our environment). If I used "update encrypted = yes", "encrypt passwords" then Windows 95 users can login with NIS password but not for NT users. How to

> On Jul 12, 2017, at 6:58 PM, Ng, Kelvin Sai-cheong <kscng at 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

Bert, The 'degree' argument follows the "..." argument in the function declaration: poly(x, ..., degree = 1, coefs = NULL, raw = FALSE, simple = FALSE) Generally, any arguments after the "..." must be explicitly named, but as per the Details section of ?poly: "Although formally degree should be named (as it follows ...), an unnamed second argument of length 1

On Mon, Jun 20, 2016 at 4:14 AM, Sanjoy Das <sanjoy at playingwithpointers.com> wrote: > Hi Vivek, > > [Dropping firefox-dev, since I don't want to spam them] > > vivek pandya via llvm-dev wrote: > > Measure W/O IPRAWITH IPRA > > ======================== > > Total Build Time76 mins82.3 mins8% increment > > Octane v2.0 JS Benchmark Score (higher is

There is a very useful and apparently fundamental feature of R (or of the package pls) which I don't understand. For datasets with many independent (X) variables such as chemometric datasets there is a convenient formula and dataframe construction that allows one to access the entire X matrix with a single term. Consider the gasoline dataset available in the pls package. For the model

Marc: 1. I am aware of the need to explicitly name arguments after ... -- see the R Language definition where this can be inferred from the argument matching rules. 2. I am aware of the stated exception for poly(). However: > x1 <- runif(20) > x2 <- runif(20) > mx <- cbind(x1,x2) > poly(mx,2) Error in poly(dots[[i]], degree, raw = raw, simple = raw) : 'degree'

Running R 2.5.1 on WinXP with Tinn-R, and using Sweave via MikTex. I am having trouble with the code below: ------------------------------------------------------- <<lowerCI95>>= lowerCI95713 <- t.test(data713, alternative="greater") lowerCI95713.bound <- lowerCI95713$conf.int[1] @ Thus a lower 95\% confidence bound on the mean octane concentration is

Hi Listers, I am trying to reflect a PCA biplot in the x-axis (i.e. PC1) but am not having much success. In theory I believe all I need to do is multiply the site and species scores for the PC1 by -1, which would effectively flip the biplot. I am creating a blank plot using the plot command and accessing the results from a call to rda. I then use the calls to scores to obtain separate site and

Hi. I have an object. I think it is a list. > str(corTFandPCA) num [1:922, 1:5] -0.0226 -0.0504 -0.0208 -0.0582 -0.0257 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:922] "abdomen.2" "abdomimal.3" "abdominal.4" "aberration.5" ... ..$ : chr [1:5] "PC1" "PC2" "PC3" "PC4" ... I want to order it

On Mon, Jun 20, 2016 at 10:05 PM, Sanjoy Das <sanjoy at playingwithpointers.com > wrote: > Hi Vivek, > > vivek pandya wrote: > > > For Octane and Kraken I have run them 4 times and above result is > > geometric mean. For Octane standard deviation (SD) is > > 918.54 (NO_IPRA) and 597.82 (With_IPRA). For Kraken unfortunately I > > don't have readings