similar to: question about dataframe ("sensory") in PLS package

Dear all, I am trying to calculate the fitted values using a ridge model (lm.ridge(), MASS library). Since the predict() does not work for lm.ridge object, I want to get the fitted_value from the coefficients information. The following are the codes I use: fit = lm.ridge(myY~myX,lambda=lamb,scales=F,coef=T) coeff = fit$coef However, it seems that "coeff" (or "fit$coef") is

Hi, I' am interested in differences between sample's result when samples consist of full elements and consist of only distinct elements. When sample consist of full elements it take about 120 sec., but when consist of only distinct elements it take about 4.5 or 5 times more sec. I expected that opposite of this result, because unique(sample) has less elements than full sample. Code as

Hi everyones, my function like; e <- rnorm(n=50, mean=0, sd=sqrt(0.5625)) x0 <- c(rep(1,50)) x1 <- rnorm(n=50,mean=2,sd=1) x2 <- rnorm(n=50,mean=2,sd=1) x3 <- rnorm(n=50,mean=2,sd=1) x4 <- rnorm(n=50,mean=2,sd=1) y <- 1+ 2*x1+4*x2+3*x3+2*x4+e x2[1] = 10 #influential observarion y[1] = 10 #influential observarion data.x <- matrix(c(x0,x1,x2,x3,x4),ncol=5) data.y

Hello! I need help to use the package pls.pcr in R. I installed R in an IRIX 6.5, using the version of R 0.64.1 from sgifreeware(I didn't get to install the newest version using make). I need to use the package pls.pcr and when I give the command: # R R : Copyright 1999, The R Development Core Team Version 0.64.1 (May 8, 1999) R is free software and comes with ABSOLUTELY NO

Dear list, I have a question concerning the above mentioned methods in the pls package with respect to the loadings matrix produced by the call. In some work I am doing I have found that the values produced are nearly of the same magnitude but of opposite sign. When I use the example data (sensory) I find this result reproduced. I am prepared to work this through but I have a feeling that

I am a beginner in R, so please don't step on me if this is too simple. I have two data sets datax and datay for which I created a qqplot qqplot(datax,datay) but now I want a line that indicates the perfect match so that I can see how much the plot diverts from the ideal. This ideal however is not normal, so I think qqnorm and qqline cannot be applied. Perhaps you can help? Ralf

Dear all, I have a question about how to get a matrix by combining a large number of columns from a data file. Suppose I read a file which have 1000 columns by: test = read.table("dat.txt", header=F) I know I could use "cbind()". It's easy to do when the number of columns is small (i.e. cbind(test$V1, test$V2)). But how about build a matrix "X" by combine the

Hi Everyone, When I have a load of functions which have various arguments passed via the ellipsis argument it keeps on assigning them as symbol making them unusable to the function. My current work around involves using do.call but this is rather cumbersome. Does anyone know why it suddenly changes the types to symbol and if there is a way to get the actual data pointed to by the symbol? (I

Dear all, Does anyone knwo how to add error bar to the data point in a simple xyplot? Right now, I have a .dat file including both the data points and their standard deviation and read it in R. I tried function arrows(). But it didn't gave me any arrows. Thanks for the help! Jeny

Version 2.0-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Version 2.0-0 of the pls package is now available on CRAN. The pls package implements partial least squares regression (PLSR) and principal component regression (PCR). Features of the package include - Several plsr algorithms: orthogonal scores, kernel pls and simpls - Flexible cross-validation - A formula interface, with traditional methods like predict, coef, plot and summary - Functions

Actually what I meant in my original loop, that there is a dependency between every two consecutive iterations. So, how the loop vectorizer says 'we can vectorize this loop'? for(int k=20;k<50;k++) dataY[k] = dataY[k-1]; From: Henrique Santos [mailto:henrique.nazare.santos at gmail.com] Sent: Sunday, November 03, 2013 4:28 PM To: Sara Elshobaky Cc: <llvmdev at

Hi Sarah, the loop vectorizer runs not on the C code but on LLVM IR this c code was lowered to. Before the loop vectorizer runs many other optimization change the shape of this IR. You can see in the LLVM IR you referenced below, a preceding LLVM IR transformation has change your loop from: > for(int k=20;k<50;k++) > dataY[k] = dataY[k-1]; to > int a = d[19]; >

Hello, I was trying to trace the Loop vectorizer of the LLVM, I wrote a simple loop with a clear dependency. But found that the debug shows that 'we can vectorize this loop' Here you are my loop with dependency: for(int k=20;k<50;k++) dataY[k] = dataY[k-1]; And the debug prints: LV: Checking a loop in "main" LV: Found a loop: for.body4 LV: Found an

Notice that the code you provided, for globals and stack allocations, at least, is semantically equivalent to: int a = d[19]; for(int k = 20; k < 50; k++) dataY[k] = a; Like so, the load you see missing was redundant, probably hoisted by GVN/PRE and replaced with "%.pre". H. On Sun, Nov 3, 2013 at 11:26 AM, Sara Elshobaky <sara.elshobaky at gmail.com>wrote: >

How do you install a package from CRAN ? I want to install pls.pcr, so I have downloaded pls.pcr_0.1.1.tar.gz but when I try to install it using the install package(s) from local zip file(s) option it says : > install.packages(choose.files('',filters=Filters[c('zip','All'),]), .libPaths()[1], CRAN = NULL) Error in file(file, "r") : unable to open connection

Dear Sir / Madam, I am new for R coding. Kindly help me out in sorting out the following problem. There are 50 rows with six coloumns(you could see in the attached .txt file). I wish to go for filtering this 50 rows for any one of the six coloumns satisfying the value >= 64. I need to have a final table with rows having >= 64 value in any one of the six coloumns and the rest could be

Hello all, I have searched the archives for a similar problem to no avail. I could use your help. I have a bunch of vectors organized into two matrices, x and y. These vectors (as rows) consist of combinations of elements such that order does not matter. I want to create a third matrix from the first two, which is basically all the rows in x and all the rows in y, excluding the rows that

Here is my code # determine the DDOA measurements for(e in 1:numSensors) { for(f in 1:numSensors) { if((combos[e,f]==1) { # true distance between each sensor and the target truedistance[e]<-sqrt((targetX-sensorX[e])^2+(targetY-sensorY[e])^2) # add an error that has a N(0, sigma^2) distribution truedistance[e]<-(truedistance[e]+rnorm(1,

Dear list I am using the mvr function of the package pls.pcr to compute PLS resgression using a X matrix of gene expression variables and a Y matrix of medical varaibles. I would like to obtain the R2 (sum of squares captured by the model) and Q2 (proportion of total sum of squares captured in leave-one-out cross validation) of the model. I am not sure if there are specific slots in the