similar to: Efficient way to perform linear regressions

Hi R people.   I have a problem. What can I create by using functions the combinations of distances in multiple comparisons tests such as duncan multiple range test?   cur=sample(rnorm(15),15,replace=TRUE) varr=factor(c(rep("var1",5),rep("var2",5),rep("var3",5))) dat<-data.frame(cur, varr) lmm<-lm(cur~ varr,data=dat)

cv.fold<-function(i, size=3, rang=0.3){ cat('Fold ', i, '\n') out.fold.c <-((i-1)*c.each.part +1):(i*c.each.part) out.fold.n <-((i-1)*n.each.part +1):(i*n.each.part) train.cv <- n.cc[-out.fold.c, c(2:2401, 2417)] train.nv <- n.nn[-out.fold.n, c(2:2401, 2417)] train.v<-rbind(train.cv, train.nv) #training data for feature

HI, Dear R community, I am writing the following function to create one data set(*tree.pred*) and one vector(*valid.out*) from loops. Later, I want to use the data set from this loop to plot curves. I have tried return, list, but I can not use the *tree.pred* data and *valid.out* vector. auc.tree<- function(msplit,mbucket) { * tree.pred<-data.frame()

Dear community, I have one file named ca_boost_feature.txt, Feature selection (Boosting:0.0025,5)! H.2.C C.1.D C.3.R E.0.N C.2.S C.0.G H.3.G log file: ep If I want to use the second line of this file, how to read it into R? varr<-read.table("/home/cdu/operon/carbonic/ca_boost_feature.txt", sep=" ", skip=1, header=F, strip.white=TRUE, nrows=1) Warning message: In

> It's the configuration part that I was looking for some help with, but > as noted I can install neither winesetuptk nor wineinstall You don't need winesetuptk or wineinstall anymore, because wine automatically sets up a .wine directory with the appropriate contents. Also, the wine config file isn't needed to successfully run wine anymore. If you don't have a .wine

Dear R-devel, It seems that lsfit incorrectly reports coefficients when the input matrix 'x' is rank-deficient, see the example below: ## here values of 'b' and 'c' are incorrectly swapped > x <- cbind(a=rnorm(100), b=0, c=rnorm(100)); y <- rnorm(100); lsfit(x, y)$coef Intercept a b c -0.0227787 0.1042860 -0.1729261 0.0000000 Warning

I'm trying to extract the points above and below a particular lsfit. I can only get the residuals from the original fit though. x = runif(100, 0, 10) plot(x) abline(lsfit(1:100, test)) abline(lsfit(1:100, test + sd(test))) #I want the points above THIS line. Is there a way to use the coefficients from the fit to do this? Thanks for any help.

Hi, in R-3.0 I get the following error when calling lsfit with more observations than variables, which seems to come from an error in the formatting of the error message (note that this was not happening in 2.15.3): > nobs <- 5; nvar <- 6; lsfit(matrix(runif(nobs*nvar), ncol=nvar), runif(nobs), intercept=FALSE) Error in sprintf(ngettext(nry, "%d response", "%d

Hello experts, as newcomer in pca, i have a question, concerning the princomp algorithm. With a dataset "r" containing 18 "input" parameters and 1 "output" parameter r[19], i got with the following fit ls <- lsfit(r[1:18],r[19]); lsdiag <- ls.diag(ls); lsdiag$std.dev a prediction error of: [1] 8.879561 what is quite reasonable. If i take only two

Not really r-specific: Z = (b1 - b2) / SQRT ( SEb1^2 + SEb2^2) -------Original Message------- From: Gijsbert Stoet <stoet at volition.wustl.edu> Sent: 07/20/03 09:51 PM To: r-help at stat.math.ethz.ch Subject: [R] how to test whether two slopes are sign. different? > > Hi, suppose I do want to test whether the slopes (e.g. determined with lsfit) of two different population are

This is not a solution but your lsfit attempt #Error in lsfit(A, b) : only 3 cases, but 4 variables lsfit(A,b) gave that error because lsfit adds a column of 1 to its first argument unless you use intercept=FALSE. Then it will give you an answer (but I think it converts your sparse matrix into a dense one before doing any linear algebra). Bill Dunlap TIBCO Software wdunlap tibco.com On

To the purpose of fitting a 2nd order polynomial (a + b*x + c*x^2) to the chunk of signal falling in a 17 consecutive samples window I wrote the following very crude script. Since I have no previous experience of using Least Square Fit with R I would appreciate your supervision and suggestion. I guess the returned coefficients of the oolynomial are: a = -1.3191398 b = 0.1233055 c = 0.9297401

ls.print produces error that I don't seem to be able to trace. Output of the commands as follows: (hyeung is a 24x2 matrix of data) ------------------------------------------------- > summary(hyeung) x.1 x.2 Min. : 28.0 Min. : 10.0 1st Qu.: 72.0 1st Qu.: 87.5 Median : 86.5 Median : 92.5 Mean : 81.0 Mean : 82.5 3rd Qu.: 97.0 3rd Qu.:100.0 Max.

ls.print produces error that I don't seem to be able to trace. Output of the commands as follows: (hyeung is a 24x2 matrix of data) ------------------------------------------------- > summary(hyeung) x.1 x.2 Min. : 28.0 Min. : 10.0 1st Qu.: 72.0 1st Qu.: 87.5 Median : 86.5 Median : 92.5 Mean : 81.0 Mean : 82.5 3rd Qu.: 97.0 3rd Qu.:100.0 Max.

I have a situation in R where I would like to find any x (if one exists) that solves the linear system of equations Ax = b, where A is square, sparse, and singular, and b is a vector. Here is some code that mimics my issue with a relatively simple A and b, along with three other methods of solving this system that I found online, two of which give me an error and one of which succeeds on the

I'm using R 2.2.0 on Windows. Doing some conversions of help files. Internal comments indicate that the Sd2Rd conversion is "Converted by Sd2Rd version 1.21." I'm converting .d -> .Rd .sgml -> .Rd using Sd2Rd, then checking by using Rdconv to convert .Rd back to .d or .sgml. Here are errors in some of the conversions. The most significant errors are in .Rd to .sgml.

Dear all, I'm new on R and this mailing list. We work on spatial rainfall estimation with R and Grass. We have a problem with the krige function from the sgeostat package. We would like to limit the estimated area with a polygon limit. I use a 50 points polygon to describe my work area. The krige function work quiet well without limit. But if I use this option I have the following error

Hi folks, Wish y'all a Happy New Year 2010! I need some help with the following: Say I have lots of data sets, on which I have to apply a certain function on the same set of columns in each of the data set. Let's take, for ex, the typical data set is: df1 <- as.data.frame(cbind(rnorm(10),rnorm(10))) names(df1)[1] <- "A" names(df1)[2] <- "B" There are many

Dear list I am sorry to have to ask this question, but I have not been able to find a solution to what seems a simple problem. I have created a lattice plot of a number of regression points and lines using a function containing panel.xyplot and panel.lmline. The result is what is expected , but I cannot figure out how to obtain the coefficients of each of the regression lines. Any help

Hello, I am working on a project to create some scatter plots. I have syntax for 26 plots, and 22 of them display as they should. But here, for example, is a sample of the command syntax I am using: good <- complete.cases(affect1,adh1scr) plot (jitter(affect1,2.0),jitter(adh1scr,1.0),xlim=c(1,35),ylim=c(1,35),pch=1 6, main='Adherence Score by Affectiveness Level - Visit 1',