similar to: adjust secondary y-axis bounds to minimize visual residuals

Hello, I was unable to find clues to my problem in ?optim. Using the data and code below, I get an error ("system is exactly singular") when a particular line of code is left in, but have found that 'optim' works when I comment it out. The line of code in question is after the closeAllConnections() line of code and contains a call to "na.approx" from the zoo package.

Dear list members, I am new member and fairly new into R world! I hope what I have is not beyond the purpose of this list. I did first search for similar experimental designs without success. I want to perform an ANOVA analysis using the aov() function. I am not 100% sure that I have it right. If anyone can help me, that will be greatly appreciated. My design is not balanced for any of the

I am having difficulty understanding how I would constrain a data set by filtering out 'records' based on certain criteria. Using SQL I could query using 'select * from my.data where LithClass in ('sand', 'clay')' or some such. Using subset, there seem to be ghosts left behind (that is, all of the LithClass *.Labels* remain after subset) > dput(tcc)

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hello everyone, I have tried several ways of doing this and searched the documentation and help lists and I have been unable to find an answer or even whether it is possible to do it. I am pasting together a formula and I need to insert double quotes around the strings. Here's an example: location <- c("AL", "AK", "MA", "PA") v=2 test <-

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

Hi all, I have been chipping away at a problem I encountered in calculating rates per year from a moderately large data file (46412 rows). When I ran the following command, I got obviously wrong output: interval<- c(NA,as.numeric(diff( strptime(mkdf$MEAS_DATE,"%d/%m/%Y")))/365.25) The values in MEAS_DATE looked like this: mkdf$MEAS_DATE[1:10] [1] 1/5/1962 1/5/1963

On Thu, May 23, 2013 at 03:40:00PM +0200, Duncan Sands wrote: > Hi Jack, > > On 23/05/13 15:37, Jack Howarth wrote: >> Below are the results for the Polyhedron 2005 benchmarks compiled with llvm/compiler-rt/dragonegg 3.3svn at r182439 against current >> FSF gcc 4.7.3svn and 4.8.1svn. The only major bug remaining in the dragonegg 3.3svn support for gcc 4.8.x is

Hi, forgive me if someone has already posted about this but I have had a look and cannot find the answer, also I am very new to R and been getting the grips with this. I have been trying to use Adonis to find out if there are significant difference between groups on data that I have analyses with NMDS, and have been struggling with getting this to work and understanding what is going on. I am

I have a problem with R. I try to compute the confidence interval for my df. When I want to create the plot I have this problem: Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ. I try this code: library(dplR) df.rwi <- detrend(rwl = df, method = "Spline",nyrs=NULL) write.table(df.rwi,file="rwi.txt",quote=FALSE,row.names=TRUE)

Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values > dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,

Hello, I probably have a syntax error in trying to generate an expected survival curve from a weighted cox model, but I can't see it. I used the help sample code to generate a weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error

Hello, Using this data: http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt and the following code i got the image at the end of this message: US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep=" ") US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE)

Hello, all. I'm new to R and just beginning to learn to write functions. I know I'm out of my depth posting here, and I'm sure my issue is mundane. But here goes. I'm analyzing the American National Election Study (nes), looking at mean values of a numeric dep_var (environ.therm) across values of a factor (partyid3). I use ddply from plyr and wtd.mean from Hmisc. The nes requires a

Hello list, I have the following function which, as you can see, uses mean: meanratings <- round(apply(stack03[,c(102:121)],2,function(x) (tapply(x ,actcode, mean, na.rm=T))), digits=1) The above function yields the following output: q27a q27b q27c q27d q27e q27f q27g q27h q27i q27j q27k q27l q27m q27o q27p 1 7.8 8.1 7.7 7.9 7.9 NaN NaN 8.4 7.8 7.0 7.6 NaN NaN 7.1 6.0 2

Below are the results for the Polyhedron 2005 benchmarks compiled with llvm/compiler-rt/dragonegg 3.3svn at r182439 against current FSF gcc 4.7.3svn and 4.8.1svn. The only major bug remaining in the dragonegg 3.3svn support for gcc 4.8.x is http://llvm.org/bugs/show_bug.cgi?id=15980 which results in unresolved symbols for _iround and _iroundf in the aermod and rnflow testcases. Note that this

Hello R-users: Could you please tell me how can I extract the "df (degree of freedom)" and "estfun (estimating functions)" for the following lmer (or lmer2) model? wtd.mixed<-lmer(ddimer~race+steroid+psi+sofa+apache + (1|subject), method="ML", data=final, cluster="id", weights=w) I tried the following codes: - for the degree of freedom (erorr

Hello list, how could this happen? The Server doesn't respond from time to time with a high load avarage. We found a suspicious smbd process: top - 13:43:07 up 1 day, 2:27, 5 users, load average: 32.49, 58.41, 37.95 Tasks: 1196 total, 5 running, 1190 sleeping, 0 stopped, 1 zombie Cpu0 : 14.7% us, 3.8% sy, 0.0% ni, 79.8% id, 1.3% wa, 0.0% hi, 0.3% si Cpu1 : 1.3% us, 84.6%

Hi All, I would like to use Kennard-Stone algorithm for splitting a dataset. > mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/binary.csv ")) > library("soil.spec") > ken.sto(mydata,per.n=0.3) Error in ken.sto(mydata, per.n = 0.3) : subscript out of bounds I found that other people run into this problem as well:

hi, I don't know what I am doing wrong, but with that code; x1 <- c(1.60, 0.27, 0.17, 1.63, 1.37, 2.00, 0.90, 1.07, 0.89, 0.43, 0.37, 0.59, 0.47, 1.83, 1.79, 0.90, 0.72, 1.83, 0.23, 1.97, 2.03, 2.19, 2.03, 0.86) x2 <- c(1.30, 0.24, 0.20, 0.50, 1.33, 1.87, 1.30, 0.75, 1.07, 0.43, 0.37, 0.87, 1.40, 1.37, 1.63, 0.80, 0.57, 1.60, 0.39, 2.03, 1.90, 2.07, 1.93, 0.93) model <-