similar to: nnet function

Hi everyone, I am trying to build a R library called nnNorm but I have some troubles checking and installing it. Here is the setup: If I don't use a inst\doc directory(with the vignettes files) in my source, the install step is working fine: C:\test>RCMD INSTALL nnNorm ---------- Making package nnNorm ------------ adding build stamp to DESCRIPTION installing R files installing

Hi everyone, According to R reference manual, the nnet function uses the BFGS method of optim to optimize the neural network parameters. I would like, when calling the function nnet to tell the optim function not to produce the tracing information on the progress of the optimization, or at least to reduce the frequency of the reports. I tried the following: a) nnet default > x<-rnorm(20)

Hi all, I am trying to run R CMD check on a package which passes R CMD INSTALL. The check stops because of a parsing problem in the example of a given function at this line: return(res[res$ID %in% list$targetGeneSets,]) The code is ok, since it runs if I paste it in R. Is this a known parsing issue in R CMD check? Thanks, Adi > sessionInfo() R version 2.13.0 (2011-04-13) Platform:

Hi all, I have a dataset in which the output Y is observed on two groups of patients (treatment factor T with 2 levels). Every subject in each group is observed three times (not time points but just technical replication). I am interested in estimating the treatment effect and take into account the fact that I have repeated measurements for every subject. If I do this with repeated measures

Top posting... While I don't really see any details that indicate this is the problem, systemd-resolved causes the packaged 18.04 samba to fail to start [at least in a full AD setup.] That's because system has a full DNS resolver, and Samba also has it's own DNS resolver. When they both try to start on the same port, the first running wins [systemd] and Samba exits. Since you're

Thanks for the response. I think  found and fixed the problem, but I need to do some more testing tomorrow. It seems that the "handle_name_resolve_order: WARNING: Ignoring invalid list value 'hosts'  for parameter 'name resolve order'" is not really a warning and it causes testparm to stop processing the smb.conf. I think that is also what caused the daemons to fail.

Dear UseRs, I wrote following function in order to solve Data Envelopment Analysis. Reason for posting is that the function is slow when nrow(dat) is large. I wonder if other functions could substitute the for() loop in the code, such as mapply(). Can anybody help to rewrite the dea() function as efficiently as possible? The code is as follows:

Dear useRs, I am trying to build my package (nonpareff) which deals with some models of data envelopment analysis. The building worked well, but checking complains when it tests examples. Zipped nonparaeff.Rcheck is attached. Following is the log. --------------------------------------------- arecibo:tmp arecibo$ R CMD build nonparaeff/ * checking for file 'nonparaeff/DESCRIPTION' ...

Dear useRs, I am trying to build my package (nonpareff) which deals with some models of data envelopment analysis. The building worked well, but checking complains when it tests examples. Zipped nonparaeff.Rcheck is attached. Following is the log. --------------------------------------------- arecibo:tmp arecibo$ R CMD build nonparaeff/ * checking for file 'nonparaeff/DESCRIPTION' ...

I ungraded my Linux Operating system from Ubuntu 16.04 LTS to 8.04 LTS Samba will not start after an upgrade to 18.04. My samba is running as an NT style member server server with smbd nmbd and winbindd all running. None of them will start. It worked this morning. This morning it was running Version 4.3.11-Ubuntu This afternoon after the upgrade it's Version 4.7.6-Ubuntu The logs in

Dear R-users, I computed a simple mixed models which was: mod<-lmer(nb ~ site + (1|patelle),tr) The output was: Linear mixed-effects model fit by REML Formula: nb ~ site + (1 | patelle) Data: tr AIC BIC logLik MLdeviance REMLdeviance 1157.437 1168.686 -574.7184 1164.523 1149.437 Random effects: Groups Name Variance Std.Dev. patelle

Dear all, I get an error message when I run my model and I am not sure what to do about it. I try to determine what factors influence the survival of voles. I use a mixed-model because I have several voles per site (varying from 2 to 19 voles). Here is the model: ### fm5 <-lmer(data=cdrgsaou2, alive~factor(pacut)+factor(agecamp)+factor(sex)+ResCondCorp+(1|factor(cdrgsa ou2$ids)),

Dear all, I ran the following model without any problem previously to the update of lme4: fm2<-lmer(data=NGud,family=poisson, seed~hab*seedtray +(1|site)+(1|site:hab)) I have 25 sites, 2 habitats ("hab") per site, 8 seedtrays per habitat (4 as control, and 4 as treatment), and I'm interested in comparing the number of seed in seedtrays as a function of the treatment and its

Hi, I'm trying to ouput to a filled with a fixed precision: eg. if I have data x=c(1.0,1.4,2.0), I want to be able to ouput the following to a file: 1.00000000000000 1.40000000000000 2.00000000000000 I was wondering if there was a function to do this in R? Thanks, Richard Richard Hedger Département de Biologie Université Laval Québec, Canada, G1K 7P4 [[alternative HTML version deleted]]

Hello, I'm actually using the "Step" procedure in R for multiple regression analysis. I'm using the stepwise selection which alternates between forward selection and backward elimination (direction "both" in the step procedure). I would like to know which F-levels R is using to enter and then to remove variables? I also would like which is the procedure to change

Hello alls, I found in the literature a technique that has been evaluated as one of the more robust to assess statistically the significance of the loadings in a PCA: bootstrapping the eigenvector (Jackson, Ecology 1993, 74: 2204-2214; Peres-Neto and al. 2003. Ecology 84:2347-2363). However, I'm not able to transform by myself the following steps into a R program, yet? Can someone could help

The Wine development release 3.11 is now available. What's new in this release (see below for details): - More debugger support for Wow64 processes. - Support for sha256/sha384 hashes in ECDSA signatures. - Better reporting of hyper-threaded CPUs. - Improvements to the standard Task Dialog. - Various bug fixes. The source is available from the following locations:

Dear R people, I am using tune.nnet from e1071 package to tune the parameters for nnet. I am using the following syntax: tuneclass <-c(rep(1,46),rep(2,15)) tunennet <-tune.nnet(x=traindata,y=tuneclass,size=c(50,75,100),decay=c(0,0.005,0.010),MaxNWts = 20000) Here traindata is the training data that I want to tune for nnet which is a matrix with 61 rows(samples) and 200

Hello All, I would like to know what fit criterion (abstol arg) is in nnet. Is it the threshold for the difference btw the max output and target values? Is the value at each iteration also the difference btw max of output and target values over all output units (case of multiple classes)? How could value displayed at each iteration be related to SSE and abstol be related to threshold SSE,

Hi, I am trying to run a nnet algorithm but when I try to use the predict function with type='class', it gives the following error: fit <- nnet(y~., size = 1, data = train.set, rang = 0.5, maxit=200, decay = 0) predict<-predict(fit,test.set,type='class') Error in predict.nnet(fit, test.set, type = "class") : inappropriate fit for class I couldn't figure