similar to: mvr error in PLS package

All, I am working with NIR spectral data and it was great to find that the example in ?plsr also used spectral data. Unfortunately, I am having difficulty figuring out how the "yarn" dataset is structured to allow for the plsr model to read: library(pls) data(yard) yarn.oscorespls <- mvr(density ~ NIR, 6, data = yarn, validation = "CV", method = "oscorespls")

I am attempting to create a formula using as.formula for a PLS analysis. I have used the code below successfully, but in a previous R version and with many fewer predictors. Any help getting all of these predictors into one formula would be greatly appreciated. TC.fmla <- as.formula(paste("TC ~ ", paste(vars, collapse= "+"))) As I mentioned, this code worked fine in a

I am attempting to run principal components analysis on a dataset of spectral reflectance (6 decimal places). I imported the data using read.table and there are both column and row headers. When I run princomp I receive the following error: Error in cov.wt(z) : 'x' must contain finite values only Where am I going wrong? Ross

I am attempting to write a routine where I can run PAM (partition around mediods) on a dataset containing multiple soil cores and PCA spectral data from several depths per core. I want to run PAM on each individual core, so I need to group the data by core to run the analysis. Below is an example of my data structure: Lab.id PC1 PC2 PC3 MAT057.2.5 2.438454966 -1.011182986 -3.040881377

I am new to Linux (not to R) and recently installed Mandriva Spring 2007 on my partitioned hard drive. My next objective is to install R in the Linux environment, unfortunately Mandriva is not one of the Linux distributions available for download... Could someone please let me know which distribution I should use? Thanks. Jonathan --------------------------------- Boardwalk for $500?

All, I am a new user to Linux but I am familiar with R. I have previously used and installed R on a Windows platform without problems. I recently set up a dual boot system (XP_64, Mandriva) to run R on a Linux platform in order to more efficiently handle large datasets. I have not done compiling before, but read the R instructions and followed to my best ability. I downloaded the most recent

All, Apparently the attachment did not make it through the list serve. I am having difficulty installing R-2.4.1 on Mandriva Linux 2007 Discovery. Thanks to the help of Doug Bates I got further along the path (Thanks Doug!!). I now cannot figure out which line of code needs modified in order for configure to complete. Please see below for the last several lines of output. checking whether

Dear developeRs, I maintain a package 'pls', which has a main fit function mvr(), and functions plsr() and pcr() which are meant to take the same arguments as mvr() and do exactly the same, but have different default values for the 'method' argument. The three functions are all exported from the name space. In the 'pre namespace' era, I took inspiration from lm() and

What version of R, what version of pls.pcr, and on what OS? Have you checked whether your versions of software are up to date? I get: > n <- 1350 > p <- 180 > y <- rnorm(n) > x <- matrix(sample(0:1, n*p, replace=TRUE), n, p) > fit <- mvr(x, y, method="SIMPLS", validat="none", ncomp=2) > xt <- matrix(sample(0:1, 312*p, replace=TRUE), 312,

Hello, I am trying to understand how to utilize the "mvr" function in the pls Package of R. I am utilizing the R "pls Package" document dated 18 May 2005 as guidance. My data set consists of a 12 x 12 data frame created from reading in a table of values. I have read the data in via the command: volumes <- read.table("THA_vol.txt", header = TRUE) and then

Dear list, given this formula: > fmla <- formula(y1 ~ spp1 + spp2 + spp3 + spp5) > fmla[[3]] spp1 + spp2 + spp3 + spp5 is this the intended behaviour of as.character: > as.character(fmla[[3]]) [1] "+" "spp1 + spp2 + spp3" "spp5" ? Where does the extra "+" come from? > as.character(fmla) [1] "~"

Greetings, I have been exploring the use of the caret package to conduct some plsda modeling. Previously, I have come across methods that result in a R2 and Q2 for the model. Using the 'iris' data set, I wanted to see if I could accomplish this with the caret package. I use the following code: library(caret) data(iris) #needed to convert to numeric in order to do regression #I

Thanks a lot for help in advance. I am switching from matlab to R and I guess I need some time to get rolling. I was wondering why this code : > fit.0 <- lm( Response ~ 1, data = ds3) > step(fit.0,scope=list(upper=~.,lower=~1),data=ds3) Start: AIC= -32.66 Response ~ 1 Call: lm(formula = Response ~ 1, data = ds3) Coefficients: (Intercept) 1.301 is not working

Hello, I am trying to "paste" together a formula to use in the mob function of party. This means the formula will be of the form y ~ x1+ ...+xM | z1+..zN. I am doing some preliminary fits of y ~ x1+ ...+xM, then want to add the conditional part of the equation using update(). Here's the test code: var1 <- 1:78 x1 <- paste("x", var1, sep="") f1 <-

Hi, I am trying to build a series of rlm models. I have my data frame and the models will be built using various coulmns of the data frame. Thus a series of models would be m1 <- rlm(V1 ~ V2 + V3 + V4, data) m2 <- rlm(V1 ~ V2 + V5 + V7, data) m3 <- rlm(V1 ~ V2 + V8 + V9, data) I would like to automate this. Is it possible to use a string in place of the formula? I tried doing: fmla

Hi, I'm trying to compile half precision program for ARM, while it seems LLVM fails to automatically generate fused-multiply-add instructions for c += a * b. I'm wondering whether I did something wrong, if not, is it a missing feature that will be supported later? (I know there're fp16 FMLA intrinsics though) Test programs and outputs, $ clang -O3 -march=armv8.2-a+fp16fml

I want use survfit() and basehaz() inside a function, but it doesn't work. Could you take a look at this problem. Thanks for your help. Following is my codes: library(survival) n <- 50 # total sample size nclust <- 5 # number of clusters clusters <- rep(1:nclust,each=n/nclust) beta0 <- c(1,2) set.seed(13) #generate phmm data set Z <- cbind(Z1=sample(0:1,n,replace=TRUE),

Hello everybody, I'm reading the .td files defining the Cortex-A57 processor, which is a subtarget of AArch64 target, and there is something confusing me in the `AArch64SchedA57.td` file. In the top of `AArch64SchedA57.td`, various processor resource are defined, as follows ``` def A57UnitB : ProcResource<1>; // Type B micro-ops def A57UnitI : ProcResource<2>; // Type

Thanks for reply. I was using LLVM 8.0. Let me try trunk and will let you know if it works. On Wed, Sep 4, 2019 at 11:19 PM Sjoerd Meijer <Sjoerd.Meijer at arm.com> wrote: > > Hi, > Which version of Clang are you using? I do get a "vfma.f16" with a recent trunk build. I haven't looked at older versions and when this landed, but we had an effort to plug the remaining

Greetings. I've written a convenience function for multicollinearity diagnosis. I'd like to report to the user the formula that is used in a regression. I get output like this: > mcDiagnose(m1) [1] "The following auxiliary models are being estimated and returned in a list:" [1] "`x1` ~ ." formula(fmla)() [1] "`x2` ~ ." I'd like to fill in the period