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Trying following example from Pinheiro and Bates in order to fit an ARMA(1,1) model: library(nlme) fm1Ovary.lme<-lme(follicles~sin(2*pi*Time)+cos(*pi*Time),data=Ovary,random=p dDiag(~sin(2*pi*Time))) fm5Ovary.lme<-update(fm1Ovary.lme,corr=corARMA(p=1,q=1)) I get follwing error message: Error in "coef<-.corARMA"(`*tmp*`, value = c(62.3428455941166, 62.3428517930051 :

Hi, I got a computational problem with lme (nlme library R 1.9.1) using corSymm(). Here is the data: [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.19639793 0.09127954 0.11733288 0.07598273 0.06545106 0.06211532 [2,] 0.22773467 0.10981912 0.16052847 0.38101187 0.18353474 0.24072918 [3,] 0.46743388 0.45733836 0.32191178 0.43356107 0.39159746 0.53984221 [4,]

Hi, I usually use lme from the nlme library. Now I have read an article about lmer in Rnews and lmer seemed to me more comfortable to use. Unfortunately, I didn't find out how to use covariance structures (e. g. corSymm(), corAR1()). Is there a way to use them similarly as in lme ? Is it implemented ? If somebody knows, please let me know. Thank you very much in advance, Stephan

I tried following commands: amp~time|subject/trial #this was the grouping structure of the data plot(dip,inner=~condition,layout=c(2,2)) after the plot command I obtained this error message: Error in if(!any(cond.max.level - cond.current.level <0)&&(row-1)* : missing value where TRUE/FALSE needed This error only occured in compination with "layout". It was no

Hi I constructed a mixed-effects model from longitudinal repeated measurements of lab values in 22 patients seperated into two groups with the groups as fixed effect using lme. I thought about using the jackknife procedure, i. e., removing any one subject and calculating the fixed effect, to assess the stability of the fixed effect and thereby validate the model. I suppose this has been done in

Dear all, I have a performance problem in terms of computing time. I estimate mixed models on a fairly large number of subgroups (10000) using lme(.) within the by(.) function and it takes hours to do the calculation on a fast notebook under Windows. I suspect by(.) to be a poor implementation for doing individual analysis on subgroups. Is there an alternative and more efficient way for doing

It should work, I have to check why it's not working. Aki On 16.11.2018 11.47, SUnsin at gv-bayern.de wrote: > With quota count and quota_clone it works, but can I use noenforcing > with quota count? > > quota = count:User quota:noenforcing > > When I test this config, I receive no quota-warning E-Mail: > > service quota-warning { > ? executable = script

dict quota is known to have this problem that it is not always updated on time. You should use quota count with quota_clone plugin instead (might require upgrade). Please remember to change password for mysql user pfadmin, as you accidentically sent it to the list. Aki > On 15 November 2018 at 20:52 SUnsin at gv-bayern.de wrote: > > > > > Hi, > > I have a working

Dear List, I´m working on a classification problem. My response has 60 levels. I`m very interested in boosted trees like AdaBoost or gradient boosting machine as implemented in the package "gbm". Unfortunately gbm is only applicable for 2-class problems. Is anybody out there who can help me? Is there a way to use gbm() for multi-class problems? Maybe there is a way to transform my

Dear List, I´m trying to implement the functionalities from WEKA into my modeling project in R through the RWeka package. In this context I have a slightly special question about the filters implemented in WEKA. I want to convert nominal attributes with k values into k binary attributes through the NominalToBinary filter ("weka.filters.supervised.attribute.NominalToBinary"). But

Hi list, I´m working on a predictive modeling task using the caret package. I found the best model parameters using the train() and trainControl() command. Now I want to evaluate my model and make predictions on a test dataset. I tried to follow the instructions in the manual and the vignettes but unfortunately I´m getting an error message I can`t figure out. Here is my code: rfControl <-

Hello all, First, the vital stats: FreeBSD 6.1-STABLE, dovecot 1.0.rc7 from ports. I have run into a vexing little problem that has brought my deployment of a shiny new dovecot server to a screeching halt. Using 'periodic' I've configured regular backups to occur using 'dump'. I have a monthly level 0, a weekly level 4, and a daily level 8. These dumps take advantage of

LLVM already implements its own version of almost all of binutils. The exceptions to this rule are objcopy and strip. This is a proposal to implement an llvm version of objcopy/strip to complete llvm’s binutils. Several projects only use gnu binutils because of objcopy/strip. LLVM itself uses objcopy in fact. Chromium and Fuchsia currently use objcopy as well. If you want to distribute your build

While it was a good move from Rails part to escape ERB <%= %> tags by default, it doesn''t seem to happen to Sprockets as well. The strange bit is that according to Sprockets documentation, it would be just a matter of naming your template as .jst.eco to enable Eco: https://github.com/sstephenson/sprockets#javascript-templating-with-ejs-and-eco Then, extracted from Eco

HI, here I have an eMail with connected to a DMZ 10.0.0.0/24 network. This server holds 10.0.0.87 There are two firewall-hosts one with CentOS 6 10.0.0.10 and one with CentOS 7 10.0.0.17 The CentOS 6 has the following iptables-rule (extract): ----------------------8<----------------------8<----------------------8< *nat -A POSTROUTING -o eth1 -j MASQUERADE -A PREROUTING -i eth1 -d

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order to

Hi, I have a working Installation with: Ubuntu 16.04 LTS Dovecot 2.2.22 MySql 5.7.24 Postfixadmin 3.2 Apache 2.4.18 Rainloop 1.12.1 I manage the E-Mail Accounts with postfixadmin in a MySql-DB. Also I use quotas with Quota Backend postfixadmin-DB (dict). Everything works fine. Now I installed a new Server with the following Versions and migrate the Configs to the new System. Ubuntu 18.04 LTS

With quota count and quota_clone it works, but can I use noenforcing with quota count? quota = count:User quota:noenforcing When I test this config, I receive no quota-warning E-Mail: service quota-warning { executable = script /usr/local/bin/quota-warning.sh # user = dovecot user = vmail unix_listener quota-warning { user = vmail group = vmail mode = 0660 } } plugin {

Hi. I was wondering if anyone might have some suggestions about how I can overcome a problem of "iteration limit reached without convergence" when fitting a mixed effects model. In this study: Outcome is a measure of heart action Age is continuous (in weeks) Gender is Male or Female (0 or 1) Genotype is Wild type or knockout (0 or 1) Animal is the Animal ID as a factor

Dear R-devel, The median() function assigns a name, "NA", to its return value if the return value is NA and the input vector has names, otherwise the names attribute is NULL. This looks strange and inconsistent with the behavior of mean(). This inconsistency becomes a problem when median() is used inside user code that relies on consistent naming convention. Thanks, Vadim > foo