similar to: Linear regression and slope from 1

Hi! I was trying to install the RWinEdt library on a Windows Vista machine which had R 2.6.0, WinEdt 5.4 and the RWinEdt1.7.8.zip file in the library folder under the ...\R\2.6.0 directory. I am able to install fine form the local zip but I can't launch winedt from within R for some reason. > utils:::menuInstallLocal() package 'RWinEdt' successfully unpacked and MD5 sums checked

Hello all, I'm using the following scan() parameters on a tab-separated text file that was generated by R. temp_file <- scan(file = outfile, sep="\t", what = character(), skip = 1, nlines = 1) The problem is that within some cells, there are cases where there are three frontslashes ( /// ). However, the file itself is tab-separated, and the exact problem is that even if I

On 06/21/2011 01:15 PM, Jan Stilow wrote: > Hello, > > Nirbheek Chauhan <nirbheek <at> gentoo.org> writes: >> [...] >> >> Every few minutes, (I guess) when applications do fsync (firefox, >> xchat, vim, etc), all applications that use fsync() hang for several >> seconds, and applications that use general IO suffer extreme >> slowdowns.

We had a recent data loss event that we're trying to analyze to learn what happened. On one of our Linux VMs, the /var partition suddenly went offline, which is never a good thing. (Later reboots revealed a corrupted filesystem that needed to be repaired, resulting in data loss.) Nothing could be written to /var, including logs in /var/log, but the VM continued to run. On that VM, we had a

I've a matrix like this: 1985 1.38 1.27 1.84 2.10 0.59 3.47 1986 1.05 1.13 1.21 1.54 0.21 2.14 1987 1.33 1.21 1.77 1.44 0.27 2.85 1988 1.86 1.06 2.33 2.14 0.55 1.40 1989 2.10 0.65 2.74 2.43 1.19 1.45 1990 1.55 0.00 1.59 1.94 0.99 2.14 1991 0.92

Hi, First off, please understand that I am not a frequent R user. I am trying to use a script generated by another program in R for a certain analysis. I have used the script successfully in the past. Recently, when trying to load the script, I receive a warning message: package 'nls' has been merged with 'stats'. As a result, program R does not do the analysis. Does anyone

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very

Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation

Hi, I am working on a data set which looks like this: > head(temp) Day Month Year PW ROW 1 1 1 1959 NA 6.40 2 2 1 1959 6.65 6.35 3 3 1 1959 2.50 3.60 4 4 1 1959 0.60 2.25 5 5 1 1959 0.85 0.30 6 6 1 1959 0.00 2.20 I am trying to extract all the rows containing NA. I can extrat all the rows without NAs in column 4 using >

Seeing upstream has an update for glibc http://rhn.redhat.com/errata/RHBA-2009-0052.html I rebuilt the glibc-2.3.4-2.41.el4_7.1.src.rpm and it produced the following rpms :- glibc-2.3.4-2.41.el4_7.1.i386.rpm glibc-common-2.3.4-2.41.el4_7.1.i386.rpm glibc-debuginfo-2.3.4-2.41.el4_7.1.i386.rpm glibc-debuginfo-common-2.3.4-2.41.el4_7.1.i386.rpm glibc-devel-2.3.4-2.41.el4_7.1.i386.rpm

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =

Hi R Users, I created interaction plots in ggplot2 and was trying to add output of two way ANOVA models, especially only interaction ( example treatment*control F(XX, XX) = xxx, p = xxx) into figures, but i was not able to add. Would you mind to help on how I can add information into each figure? I have attached the example data and the code that I used for this. dat<-structure(list(Sites

Dear Eliza, Try this: Lines1<-readLines(textConnection("1911.01.01?????? 7.87 1911.01.02?????? 9.26 1911.01.03?????? 8.06 1911.01.04?????? 8.13 1911.01.05????? 12.90 1911.02.06?????? 5.45 1911.02.07?????? 3.26 1911.03.08?????? 5.70 1911.03.09?????? 9.24 1911.04.10?????? 7.60 1911.05.11????? 14.82 1911.05.12????? 14.10 1911.06.13?????? 7.87 1911.06.14?????? 9.26

I recently upgraded from 2.41 to 2.43. I feed my Icecast server with either a live stream or from EZStream. I am now finding that track title metadata never exceeds thirty characters. Is this new, or have I got something wrong in the 2.43 configuration? I am actually using the same one I used for 2.41, and I don't ever remember seeing anything in the XML that controls length of metadata

The aggregate function for some reason will now work for me. The error I'm getting is: "Error in sort.list(y) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" agPriceList=aggregate(PriceList$Size, list(PriceList$bandNum),sum) *Price list dataframe:* dput(PriceList) structure(list(Price = c(0, 8.18, 8.27, 10.42, 10.5, 10.6, 11.13,

Hi, I'm regressing various body dimensions upon body mass using the 'lmodel2' function, as I'm keen to obtain both OLS and RMA slope values. I also wish to create a plot of the regressions, with the 95% confidence interval of both the slope and intercept. I know how to plot 95% ci bands of the OLS slope using lm with the 'predict' function and 'matlines'. Does

Greetings, I would like to use the "boot" function to generate a bootstrap confidence interval for the slope in a SLR that has a zero intercept. My attempt to do this is shown below. Is this the correct implementation of the boot function to solve this problem? In particular, should I be doing anything with the residuals in the "bs" function (e.g., using weighted residuals)?

Dear R users, Using R lme function, I found that both fixed and random effects of variable A on variable B are significant. Now, I'd like to analyze what variables are predicting differences in the slope. In other words, I'd like to know what variables (e.g., variable C) are predicting individual differences in the effects of A on B. I have many data points for A and B for each

Dear All, I fear that this is a really easy question but I do seem to go around in circles.. I have 2 points on a plot and would like to calculate the slope of the line drawn through these 2 points. that cant be so hard?! Thank you in advance, Katrin -- Katrin Fleischer Vrije Universiteit Amsterdam Faculty of Earth and Life Sciences Subdepartment Hydrolgy and Geo-Environmental Sciences Room

library(ROCR) n <- 1000 fitglm <- function(iteration,intercept,sigma,tau,beta){ x <- rnorm(n,0,sigma) ystar <- intercept+beta*x z <- rbinom(n,1,plogis(ystar)) xerr <- x + rnorm(n,0,tau) model<-glm(z ~ xerr, family=binomial(logit)) *int*<-coef(model)[1] *slope*<-coef(model)[2] # when add error you are suppose to get slightly bias slope. However when I change