similar to: lm() and factors appending

The original implementation utilies select(). In Linux select() typically supports up to 1024 file descriptors. This can be a problem when user tries to boot up many guests. Switching to poll() has minimum impact on existing code and has better scalibility. Up to 8192 file descriptors are supported in the current implementation. Signed-off-by: Wei Liu <wei.liu2@citrix.com> ---

Xen patchbot -unstable wrote: ># HG changeset patch ># User cl349@firebug.cl.cam.ac.uk ># Node ID 8fe8a99b1c2a6ea88624546ab625eaa0758e3a17 ># Parent e69cbfee4011da1648718f1f5cbe8dabb956e72a >New console transport and update xenconsoled. >Add a new console interface using a seperate shared page and event channel >instead of passing the console input/output over control

I have formulae with coefficents that I would like to update. However, I get some strange results. For example, see the following: For the formula y ~ d+ 3*r+t I want to add a variable p, so > update(y~d+0*r+t, .~.+p) produces y ~ d + t + p - 1 If the coefficient is not 0, but rather, something else - say, 3, I get the following: > update(y~d+3*r+t, .~.+p) Error in

Hi I have the problem with fitting curve to data with lm and glm. When I use polynominal dependiency, fitted values from model are OK, but I cannot recive proper values when I use coefficents to caltulate this. Let me present simple example: I have simple data.frame: (dd) a: 1 2 3 4 5 6 b: 3 5 6 7 9 10 I try to fit it to model: model=glm(b~poly(a,3),data=dd) I have following data

# I need to generate some data. I'm modeling some time series that follow a # negative exponential decay (mostly). I have 20 samples that can easily be fit with cubic splines. # What I want to do is generate many thousands of similar samples using the parameters from the splines # For instance one data sample looks not unlike this: foo.curve <- 1 * exp(-0.01 * 1:500) + 0.5

Thanks to the help of many on this list, I am now an R user and have been able to write some functioning code to do matching estimation. I have two for loops (i in 1:3, and j in 0:2). Within the loops, I had been creating matrices of relevant estimation coefficents in order to make lots of LaTeX tables. Well, now I want to be able to combine the results of many different estimations from within

Hello R users I ran more than 100 logistic regression analyses. Some of the analyses gave me this kind warning below. ########################################################### Warning messages: 1: algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, ... 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y,

Hi, I'm dealing with a datamining analysis: I've a lot of categories of product sold per week (n. week =26, n. categories about 50. my dataframe is like this: Settimana ALIMENTI..ALTRI. ALIMENTI.APROTEICI 1 1 3 19 2 2 2 0 3 3 1 22 4 4 2

Hi there, I just don't find the solution on the following problem. :( Suppose I have a dataframe with two predictor variables (x1,x2) and one depend binary variable (y). How is it possible to define a glm object (family="binomial") with a user defined logistic function like p(y) = exp(a + c1*x1 + c2*x2) where c1,c2 are the coefficents which I define. So I would like to do no

Grant references for the xenstore and xenconsole shared pages exist, but currently only xenstore uses these references. Change the xenconsole daemon to prefer using the grant reference over map_foreign_range when mapping the shared console ring. This allows xenconsoled to be run in a domain other than dom0 if set up correctly - for libxl, the xenstore path /tool/xenconsoled/domid specifies the

Dear R-user: After the fitting the Tobit model using zelig, if I use the following command then I can get the regression coefficents: beta=coefficients(il6.out) > beta (Intercept) apache 4.7826 0.9655 How may I extract the "Naive SE" from the following output please? > summary(il6w.out) Call: zelig(formula = il6.data$il6 ~ il6.data$apache, model =

Hello- Such a strange problem, can't figure it out at all. Using binomial glm models, and the step() function, so the call looks like this: sectionmodel = glm(formula = Target3 ~ S1Q12_NUM.1 + S1Q9_NUM.1 + S1Q5_NUM.1 + S1Q7_NUM.1 + S1Q8_NUM.1 + S1Q6_NUM.1 + S1Q10_NUM.1 + S1Q12_BURG.1 + S1Q12_CD.1 + S1Q4.1 + S1Q12_OTHVIOL.1 + S1Q8.1 + S1Q12_GBH.1 + S1Q11.1 + S1Q7.1 + S1Q12_THEFT.1

Hello R users I like to extract z values for x1 and x2. I know how to extract coefficents using model$coef but I don't know how to extract z values for each of independent variable. I looked around using names(model) but I couldn't find how to extract z values. Any help would be appreciated. Thanks TM ######################################################### >summary(model) Call:

> I am trying to produce a heatmap of pairwise correlations, but since the matrix is > symmetric, I only need either the upper or the lower triangle. I have scoured the > web and R documentation, but I have not been able to find a way to produce such a > figure. Is there a simple way to produce a heat map with only the part above or > below the diagonal? You might want to check

Is there any package that assists in saving and reconstituting glm and nls fits without bringing along the accompanying data? A quick search on CRAN didn't turn up anything. If not, how do other people deal with saving the coefficients of model fits? For example, I've run a glm fit that has 23 coefficents on data set that had 193,008 rows, by the time the fit was called. When I save

Hello all, Does anyone know how to constrain/force specific coefficients when running lm()? I need to run recresid() {strucchange package} on the residuals of forecast.lm, but forecast.lm's coefficients must be determined by parameter.estimation.lm I could estimate forecast.lm without lm() and use some other kind of optimisation, but recresid() requires an object with class lm.

hello everybody, I would like to fit a model to a times series (testing set) for out of sample predictions using garchFit(). I would like to keep the coefficients of ARMA/GARCH model fixed (as found by fitting the model to my training set). The arima fitting function has such an option for that (fixed=NULL) but the garchFit() doesnt. It is very important for me to keep the same coefficients

Hello. I am getting results from sem that are not correct (that's assuming that the results from my AMOS 4.0 software are correct). sem does not vary some of the parameters substantially from their starting values, and the final estimates of those parameters as well as the model chisquare value are incorrect. I've attached some code that replicates the problem. The parameters in

Hello, I want to know if two quadratic regressions are significantly different. I was advised to make the test using step 1 bootstrapping both quadratic regressions and get their slope coefficients. (Let's call the slope coefficient *â*^1 and *â*^2) step 2 use the slope difference *â*^1-*â*^2 and bootstrap the slope coefficent step 3 find out the sampling distribution above and

Josh Coalson wrote: > --- smoerk <smoerk@gmx.de> wrote: > >>i didn't find anything about tagging flac files as surround files. i >>think there should some possibility to tell the player how to play a >>multi-channel file (how to map the different channels to the speakers >>or if there some decode is needed, like for ambisonic files). > > > it