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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 am a new R user but a long time SAS user. I searched for a response to this question but no luck, so forgive me if this topic has been covered before. I am running a TukeyHSD post hoc test after running an ANOVA. I get the results of all pairwise comparisons, no problem. However, the output table is a little "busy", and I'd like to make the output easier to read. Specifically, I

Looking for a little help figuring out what's driving gaps in data after merging two xts objects (msci.m and x2). The merge statement I'm using is ... y <-merge(x2,msci.m, all=FALSE). Here's info on the output , y: head(y) t-bill msci Sep 1985 7.310 316.963 Mar 1986 6.560 463.471 Jun 1986 6.180 498.791 Jul 1987 6.200 778.898 Aug 1987 6.400 833.519 Nov 1987

I've only begun investigating R as a substitute for SPSS. I have a need to identify for each CASE the closest (or most similar) 5 other CASES (not including itself as it is automatically the closest). I have a fairly large matrix (50000 cases by 50 vars). In SPSS, I can use Correlate > Distances to generate a matrix of similarity, but only on a small sample. The entire matrix can not

Hello. I am wondering why I am getting NA for all in cors=sapply(pred,cor,y=resp). I suppose that each column in pred has NAs in them. Is there some way to fix this? Thanks > str(pred) 'data.frame':   200 obs. of  13 variables:  $ mnO2: num  9.8 8 11.4 4.8 9 13.1 10.3 10.6 3.4 9.9 ...  $ Cl  : num  60.8 57.8 40 77.4 55.4 ...  $ NO3 : num  6.24 1.29 5.33 2.3 10.42 ...  $ NH4 : num  578

Hi, I'm fitting a standard nonlinear model to the luminances measured from the red, green and blue guns of a TV display, using nls. The call is: dd.nls <- nls(Lum ~ Blev + beta[Gun] * GL^gamm, data = dd, start = st) where st was initally estimated using optim() st $Blev [1] -0.06551802 $beta [1] 1.509686e-05 4.555250e-05 7.322720e-06 $gamm [1] 2.511870 This works fine but I

Dear R users, Here is the coxme output I obtain on my survival dataset having 3 strains and 2 infection status (i: infected, ni: non infected) coxme(Surv(lay) ~ infection*strain, data=datalay, random= ~1 |block) Cox mixed-effects model fit by maximum likelihood Data: datalay n= 1194 Iterations= 3 77 NULL Integrated Penalized Log-likelihood -7270.028 -7223.859 -7218.175

> OK ... this is silly > > CentOS is an Enterprise distro and works great as a workstation. In > fact, it is just as good as Ubuntu for a desktop. I would argue that a > stable, supported for several year desktop is much better than a distro > that upgrades every 6 months. I have found just that. I was introduced to linux a couple of years ago by way of FC5 (known about it

Hi Elisa, You need to check your data.? For some 'st', the data is repeated/duplicated (I am assuming, didn't check it) especially for a particular year. dat1<-read.csv("elisa.csv",sep="\t") dat1$st<- as.character(dat1$st) ?str(dat1) #'data.frame':??? 506953 obs. of? 5 variables: # $ st?????? : chr? "AGOMO" "AGOMO"

On 11.01.2018 13:20, Hauke Fath wrote: >/On Thu, 11 Jan 2018 12:20:45 +0200, Aki Tuomi wrote: />>/Was the certificate path bundled in the server certificate? />/No, as a separate file, provided from the local (intermediate) CA: />//>/ssl_cert = </etc/openssl/certs/server.cert />/ssl_key = </etc/openssl/private/server.key />/ssl_ca =

We are currently experiencing a very huge perfomance drop on our zfs storage server. We have 2 pools, pool 1 stor is a raidz out of 7 iscsi nodes, home is a local mirror pool. Recently we had some issues with one of the storagenodes, because of that the pool was degraded. Since we did not succeed in bringing this storagenode back online (on zfs level) we upgraded our nashead from opensolaris b57

Dear R users, I have a dataset with two variables: $esan - a grouping factor with 8 levels and $reus. I'd like to do wilcox.test on this dataset as sugested Weiwei here: https://stat.ethz.ch/pipermail/r-help/2007-July/136627.html. I tried to adapt his recommendation but no succes. Can anyone help me? Regards, Iurie Malai, Senior Lecturer Department of Psychology Faculty of Psychology and

Hi all, Been using Esword for months on a self-compiled wine (the self-compilation was for WC3 hosting, but that's another story). Just today I tried to start it up as usual and it flashed the main window and crashed. Running the command from the terminal just gives me the cryptic 'segmentation fault' error. I've tried upgrading Wine to 1.15 and 1.16 both, as well as a downgrade

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Dear R users, I try to write an rcode for a paranetric weibull model with unobserved heterogeneity. The data I have are giuven below. ( The data comes from Keiding and Klein artricle published in the Statistics in Medicine 1996) . While the simple weibull model runs perfectly ( I get -2*loglikelihood 1093,905), the weibull frailty model does not run well. The code I write is :

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Some additional tests : With : -O2 -march=core2 for both gcc and llvm-gcc : LLVM is better with 10%. LLVM GCC Difference Difference % Run 1 13771597.2 13105010.6 666586.6 4.84 Run 2 13813420.8 12536327.1 1277093.7 9.25 Run 3 13769573.8 12124207.3 1645366.5 11.95 Run 4 13883222.6

Dear R community, The next release of package ff is available on CRAN. With kind help of Brian Ripley it now supports the Win64 and Sun versions of R. It has three major functional enhancements: a) new fast in-memory sorting and ordering functions (single-threaded) b) ff now supports on-disk sorting and ordering of ff vectors and ffdf dataframes c) ff integer vectors now can be used as

Dear R community, The next release of package ff is available on CRAN. With kind help of Brian Ripley it now supports the Win64 and Sun versions of R. It has three major functional enhancements: a) new fast in-memory sorting and ordering functions (single-threaded) b) ff now supports on-disk sorting and ordering of ff vectors and ffdf dataframes c) ff integer vectors now can be used as