similar to: PROC NLMIXED what package equivalent in R?

Does anyone know of some code, and examples that implement game theory/Nash equilibrium hypothesis testing using existing packages like igraph/statnet or similar? Perhaps along the lines of this article: Zhang, Y., Aziz-Alaoui, M. A., Bertelle, C., & Guan, J. (2014). Local Nash Equilibrium in Social Networks, *4*, 6224. Best, Chris Buddenhagen cbuddenhagen at gmail.com [[alternative HTML

I responded to the unhelpful suggestion "Why don't you implement and uplad the package to CRAN?" No mention of a search engine. Is this what you are commenting on Jeff? > On Jun 28, 2017, at 5:41 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > > In what way does reminding people that packages exist because others just like them contributed something

I don't think OP asked an unreasonable question at all. Civility! > On Jun 27, 2017, at 2:00 PM, Suzen, Mehmet <mehmet.suzen at gmail.com> wrote: > > Why don't you implement and uplad the package to CRAN? > > On 27 Jun 2017 17:45, "Chris Buddenhagen" <cbuddenhagen at gmail.com> wrote: > > Does anyone know of some code, and examples that

Thanks I too wondered about the tone. The first suggestion was that I should "google it" and the second, write my own code. I think if I did I'd be reinventing the wheel, (and it'd be a big challenge for me). Also, I have been searching and not found such code, despite evidence that it has been coded (just not sure if it was in R). BTW I did write to authors of the article I

Hi, I am trying to convert the following NLMIXED code to NLME, but am running into problems concerning 'Singularity in backsolve'. As I am new to R/S-Plus, I thought I may be missing something in the NLME code. NLMIXED *********** proc nlmixed data=kidney.kidney; parms delta=0.03 gamma=1.1 b1=-0.003 b2=-1.2 b3=0.09 b4=0.35 b5=-1.43 varu=0.5; eta=b1*age+b2*sex+b3*gn+b4*an+b5*pkn+u;

Why don't you implement and uplad the package to CRAN? On 27 Jun 2017 17:45, "Chris Buddenhagen" <cbuddenhagen at gmail.com> wrote: Does anyone know of some code, and examples that implement game theory/Nash equilibrium hypothesis testing using existing packages like igraph/statnet or similar? Perhaps along the lines of this article: Zhang, Y., Aziz-Alaoui, M. A., Bertelle,

Hello Chris, I was implying you are capable enough to implement it, while you have already identify a research paper. If there is no package out there, uploading to CRAN would help future user too. I am more than happy to help if you want to implement from scratch. Best, Mehmet On 27 June 2017 at 17:45, Chris Buddenhagen <cbuddenhagen at gmail.com> wrote: > Does anyone know of some

In what way does reminding people that packages exist because others just like them contributed something count as being uncivil? Terse, perhaps, since it bypassed the obvious suggestion to use a search engine, but not rude. -- Sent from my phone. Please excuse my brevity. On June 28, 2017 5:08:16 AM EDT, Boris Steipe <boris.steipe at utoronto.ca> wrote: >I don't think OP asked an

I have a list of scientific names in a data set. I would like to split the names into genus, species and subspecies. Not all names include a subspecies. Could someone show me how to do this? My example code is: a <- matrix(c('genusA speciesA', 10, 'genusB speciesAA', 20, 'genusC speciesAAA subspeciesA', 15,

Hi all, Given a data frame as... > head(veg) genus species trophia type geo zone importance 1 Sphagnum subsecundum M A En 100 2 Sphagnum denticulatum M A En 200 3 Molinia caerulea M A En 300 4 Sphagnum flexuosum M A En 400 5 Juncus squarrosus M A En 500 6

I just downloaded version 1.0.0 and several binary libraries (VR, rpart, norm, stataread) - WinNT version. I then converted a file from Stata 6.0 to R format by using the stataread library. The file converts perfectly and I was able to use the VR function lda on the dataframe without difficulty. I then tried to use the same dataframe with RPART. The model statement:

Does anyone know of example r-code/packages for carrying out analysis? Preferably this would have examples from real experimental data of two or more competing species... Thanks Chris Buddenhagen [[alternative HTML version deleted]]

Dear R friends A while a go I sent an email to the epi-list and later to the help-list and no answer could fully illuminate my question. So Im trying again with a more specific matter. Im trying to work on a script (function) to analyse data from a diagnostic test meta-analysis with random effects. This was first described by an author using SAS witn PROC NLMIXED. Im not an expert in R and much

I'm trying to run a zero-inflated regression for a continuous response variable in R. I'm aware of a gamlss implementation, but I'd really like to try out this algorithm by Dale McLerran that is conceptually a bit more straightforward. Unfortunately, the code is in SAS and I'm not sure how to re-write it for something like nlme (if at all possible - with conditions etc). Does

I don't see what's missing in my statements to add rows to a data frame and someone else will probably see what needs to be added to the statements. The data frame has this structure (without any data): $ PHYLUM : chr $ SUBPHYLUM : chr $ SUPERCLASS : chr $ CLASS : chr $ SUBCLASS : chr $ INFRACLASS : chr $ SUPERORDER : chr $ ORDER : chr $ SUBORDER :

Hello R users I'm using MuMIn but for some reason I'm not getting the adjusted confidence interval and uncoditional SE whe I use model.avg(). I took into consideration the steps provided by Grueber et al (2011) Multimodel inference in ecology and evolution: challenges and solutions in JEB. I created a global model to see if malaria prevalence (binomial distribution) is related to any

Hello! Can anyone help me. I am using the posterior.mode from the result of glmmML. It apears to be different from the BLUe estimate of the RANDOM statement in PROC NLMIXED in SAS. Why is that? Thank you Ronen [[alternative HTML version deleted]]

Dear All, reading an article by Rodolphe Thiebaut and Helene Jacqmin-Gadda ("Mixed models for longitudinal left-censored repeated measures") I have found this program in SAS proc nlmixed data=TEST QTOL=1E-6; parms sigsq1=0.44 ro=0.09 sigsq2=0.07 sigsqe=0.18 alpha=3.08 beta=0.43; bounds $B!](B1< ro < 1, sigsq1 sigsq2 sigsqe >= 0; pi=2*arsin(1); mu=alpha+beta*TIME+a i+b i*TIME;

Dear List, I am looking to calculate two things from my data frame and was after some advice. For the example below i want to know. 1. How many unique Orders/Families and Genera there are per eco-name 2. How many incidences are there for each Order/Family and Genus there are per eco-region I have 650 econame. I.e for Biak-Numfoor rain forests there are 2 orders, 2 families and two genera.

Hi everybody: I?m trying to rewrite some routines originally written for SAS?s PROC NLMIXED into LME4's glmer. These examples came from a paper by Nelson et al. (Use of the Probability Integral Transformation to Fit Nonlinear Mixed-Models with Nonnormal Random Effects - 2006). Firstly the authors fit a Poisson model with canonical link and a single normal random effect bi ~ N(0;Sigma^2).The