similar to: How to extract vectors from an arima() object and into a data frame?

I'm playing the newly released game Rage by id software on my Arch Linux 64 bit box and runs quite nicely. I was beginning to wonder if it would be possible to ply the game with controller/gamepad? What is possible/easiest to set up with wine? I have an ps3 controller could that do the job or would it be easier to get an xbox 360 controller or a completely different gamepad? Any suggestions

I have a form, with 3 fields, then in my controller I get the paramters to run a query but I don''t want to filter with paramters if they are nil or blank... I''m doing this @condition = '''' if(params.....) @condition = @condition + " myparamter = " + params[..... if(params.....) @condition = @condition + " myparamter = " +

Hi there. I am not sure if this is the right place to address my question, but I need someone how knows about the channel system of openssh. At the moment, I try to modify the openssh source to fit to my needs. Therefore I modified the openssh source so it can be called from my source like a function (simply changed "void main()" to "void ssh()"). This works perfect for the

Hi, I believe this question has been asked before, but I cant find and don't remember the answer. The problem is simple, calling 'plot.data.frame(x)' gives a nice 'matrix of scatterplots' for each pair of columns in x. for example; x <- data.frame(a=jitter(01:20), b=jitter(20:01), c=jitter(21:40), d=jitter(rep(01,20)),

Hello R-help   I am working with large data table that have the occasional label,  a particular time point in an experiment. E.g: "Time (min)", "R1 R1", "R2 R1", "R3 R1", "R4 R1" .909, 1.117, 1.225, 1.048, 1.258 3.942, 1.113, 1.230, 1.049, 1.262 3.976, 1.105, 1.226, 1.051, 1.259 4.009, 1.114, 1.231, 1.053, 1.259 4.042, 1.107, 1.230, 1.048, 1.262

Dear All, Comparing linear mixed effect models in SAS and R, I found the following discrepancy: SAS R random statement random subj(program); random = ~ 1 | Subj -2*loglik 1420.8 1439.363 random effects variance(Intercept) 9.6033 9.604662

Hello all, I have just started using fitting the PCM (Partial Credit Model) using eRm and have 2 problems which I cannot solve, I have checked everywhere on the net, but no joy: Firstly, I have fit a PCM model to 10 variables with differing response categories (3 for the first 6 items, 4 for the following 2 and 2 for the last two items). mat1 <- matrix(c(rasch_bart$bart_bowel,

Hello at all, working with a dataset I try to optimize a non-linear function with constraint. test<-read.csv2("C:/Users/Herb/Desktop/Opti/NORM.csv") fkt<- function(x){ a<-c(0) s<-c(0) #Minimizing square error for(j in 1:107){ s<-(test[j,2] - (x[1] * test[j,3]) - (x[2] * test[j,4]) - (x[3]*test[j,5]) - (x[4]*test[j,6]) - (x[5]*test[j,7]))^2 a<- a+s} a<-as.double(a)

Dear R-helpers, I try to perform glm's with negative binomial distributed data. So I use the MASS library and the commands: model_1 = glm.nb(response ~ y1 + y2 + ...+ yi, data = data.frame) and predict(model_1, newdata = data.frame) So far, I think everything should be ok. But when I want to perform a glm with a subset of the data, I run into an error message as soon as I want to predict

Hello, I have a problem finding a root of a function, which I define like this: tuki <- function(u, x, a, lambda){ if((lambda%%1>0) & u<0) {u<-(u+0i)} f <- Re(x-(a*(u)^lambda-(1-(u))^lambda)/lambda) f } What I want to do is to find the root, but without specifying the interval within which to search for it. I can do it easily in MATLAB with fsolve() or fzero() functions. I

I am attempting to run a glm with a binomial model to analyze proportion data. I have been following Crawley's book closely and am wondering if there is an accepted standard for how much is too much overdispersion? (e.g. change in AIC has an accepted standard of 2). In the example, he fits several models, binomial and quasibinomial and then accepts the quasibinomial. The output for residual

Until a weeks ago I used stata for everything. Now I'm learning R and trying to move. But, in this stage I'm testing R trying to do the same things than I used to do in stata whit the same outputs. I have a problem with the logit, applying weights. in stata I have this output . svy: logit bach job2 mujer i.egp4 programa delay mdeo i.str evprivate (running logit on estimation sample)

Hello, I would like to do a partial least square discriminant analysis (PLSDA) in R using the package "ropls" Which is in R available via the R command : source("https://bioconductor.org/biocLite.R") I try to do a PLSDA to illustrate the impact of two genders (AP,C) on 5 compounds measured in persons (samples) should be illustrated. When I try to do a PLSDA I get the warning

First of all, I have GAMs noxd<-gam(newNOX~pressure+maxtemp+s(avetemp,bs="cr")+s(mintemp,bs="cr")+s(RH,bs="cr")+s(solar,bs="cr")+s(windspeed,bs="cr")+s(transport,bs="cr"),family=gaussian (link=log),groupD,methods=REML) Then I type " summary(noxd)". and show Family: gaussian Link function: log Formula: newNO2 ~ pressure

This patch isn't complete (patch 6/6 isn't finished) so it's just for discussion, although it does compile and run. This introduces to nbdkit a concept of "filters" which can be placed in front of plugins to modify their behaviour. Some examples where you might use filters: * Serve a subset of the data, such as (offset, range) or a single partition from a disk image.

Also, this is the profile output of this Volume: gluster> volume profile mariadb_gluster_volume info cumulative Brick: laeft-dccdb01p.core.epay.us.loc:/export/mariadb_backup/brick ------------------------------------------------------------------- Cumulative Stats: Block Size: 16384b+ 32768b+ 65536b+ No. of Reads: 0 0 0

Dear friends, I used R and SAS to analyze my data through generalized linear model, and there is some difference between them. Results from R: glm(formula = snail ~ grass + gheight + humidity + altitude + soiltemr + airtemr, family = Gamma) Deviance Residuals: Min 1Q Median 3Q Max -1.23873 -0.41123 -0.08703 0.24339 1.21435 Coefficients:

Hi everyone, I have a quick and probably easy question about lme for this list. Say, for instance you want to model growth in pituitary distance as a function of age in the Orthodont dataset. fm1 = lme(distance ~ I(age-8), random = ~ 1 + I(age-8) | Subject, data = Orthodont) You notice that there is substantial variability in the intercepts (initial distance) for people at 8 years, and that

Hi list members, I saw a couple lavaan posts here so I think I?m sending this to the correct list. I am trying to run a multigroup analysis with lavaan in order to compare behavioural correlations across two populations. I?m following the method suggested in the paper by Dingemanse et al. (2010) in Behavioural Ecology. In one of the groups, lavaan returns negative variance for one path and I?m

Hello, I would like to do a partial least square discriminant analysis (PLSDA) in R using the package "ropls" Which is in R available via the R command : source("https://bioconductor.org/biocLite.R") When I try to do a PLSDA using my own data. The impact of two genders (AP,C) on 5 compounds measured in persons (samples) should be illustrated. When I try to do a PLSDA I get