similar to: Fwd: Negbin Error Warnings

Hi, I ran a negative binomial regression (NBR) using the Zelig-package and the negbin model. When I then try to use the simumlation approach using the setx () and sim() functions to calculate expected values and first difference for different levels of one of my independent variables, I get 50 errors warnings, telling me that the calculation rpois produced NAs. However, the data I use

Hey everybody, I have a problem with the combination of the commands outer() and predict(). I want to visualize the solutions of a regression modell in a matrix. Therefore I want to use the command predict for a linear modell as the function inside the command outer. I've made a small example: x = 1:10 y = 11:20 z = rnorm(10) lm.1 = lm(z ~ x*y)

Hi I have the code like I show below. The problem here is that I have a setReplacementMethod to set the value of my class slot. However, this function doesn't work when I call it within another function definition (declared by setMethod) of the same class. I do not understand this behavior that much. I'm wondering how to make this work? Any help would be really appreciated. Thank you.

Hi, say I got the function: > x=function(nbr){y<-rnorm(nbr);y1 <- mean(y);plot(y)} how can I retrieve value of y1, when I need it. I don't want: > x=function(nbr){y<-rnorm(nbr);y1 <<- mean(y);plot(y)} > y1 I want someting like: "x$y1" and then I get the value Many thanks, robert -- View this message in context:

Dear list, I am still struggling with something that should be easy: I compare two data frames with a lot of common rows and want to keep only rows that are NOT in both data frames, unique. Here are an example of these data frame. reported <- structure(list(Product = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 3L, 4L, 5L, 5L), .Label = c("Cocoa", "Coffee C", "GC",

I feel tedious when I define a S4 class and the methods. For each method, I have to call both setMethod and setGeneric (or both setReplaceMethod and setGeneric). I would like a more compact grammar so that I can reduce the key strokes. I'm wondering if there is a better way available. setClass( Class='A', representation=representation( x='numeric' )

Hi Jean-Marc, do you have any other ideas what to look for? Or do you currently debug yourself? As I already wrote, I'm out of ideas... best regards, Frank Frank Lorenz <Frank_wtal at web.de> hat am 18. Januar 2010 um 16:39 geschrieben: > Yes, I did. > > As mentioned earlier, only the enhancer inside the docoder produces a lot of overflow messages (it points to lines 68

Dear List, I want to compare and return the rows which are NOT in the two data frames. Classic methods don't work as the df have NOT the same dimensions. Here are one example of my df: reported <- structure(list(Product = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 3L, 4L, 5L, 5L), .Label = c("Cocoa", "Coffee C", "GC", "Sugar No 11", "ZS"),

Hi, i am new to the R-project but until now i have found solutions for every problem in toturials, R Wikis and this mailing list, but now i have some problems which I can't solve with this knowledge. I have some data like this: # sample data head1 = "a;b;c;d;e;f;g;h;i;k;l;m;n;o" data1 = "1;1;1;1;1;1;1;1;1;1;1;1;1;1" data2 = "2;2;2;2;2;2;2;2;2;2;2;2;2;2" data3 =

Sorry for emailing both group. As I will have a constant array of BlockAddress, what type I should use in Constant Array for its ArrayType declaration? I am creating the list in following way: unsigned int nBr = fit->second.size(); llvm::Constant *listBA[nBr]; unsigned int Idx = 0; for (std::set<llvm::BasicBlock *>::iterator it = fit->second.begin(); it != fit->second.end(); ++it)

Hi, I have a PRI euroisdn link between an Alcatel PBX and Asterisk. I'm having some trouble with overlap dialing. Suppose I dial '874053' from an Alcatel extension ('7034') where '87' is an Alcatel prefix of type "ARS Prof.Trg Grp Seiz.with overlap". I'm expecting Asterisk to receive '1004053' (where '100' is a prefix which always shows

Hello R users, I found the odfWeave package to create an odf document. It seems to be a very nice tool. So i tried to used it to create a report with multiple plot: I create an odt file with some code inside: I connect to a mysql database I get a list of projects foreach project I would like to make a plot (a map exactly) then in a R console I use the odfweave (inFile, outFile) function.

Is anybody working on a way to standardize the creation of "newdata" objects for predict methods? When using predict, I find it difficult/tedious to create newdata data frames when there are many variables. It is necessary to set all variables at the mean/mode/median, and then for some variables of interest, one has to insert values for which predictions are desired. I was at a

Hi, I have two questions on using the ff package and wonder if anyone who used ff can share some thoughts. I need to save a matrix as a memory-mapped file and load it back later. To save the matrix, I use mat = matrix(1:20, 4, 5) matFF = ff(mat, dim=dim(mat), filename="~/a.mat", overwrite=TRUE, dimnames = dimnames(mat)) To load it back, I use matFF2 = ff(vmode = "double",

Hi Jean-Marc, yes, problem exists in narrowband-mode, too. I already twiddled with max_gain, but did not have real success. I changed line 337 of ltp.c (function pitch_gain_search_3tap_vq) if (sum>best_sum && gain_sum<=max_gain) { to if (sum>best_sum && gain_sum<max_gain) { -- that stabilizes speex for 2000 Hz and 2200 Hz input on quality setting 7 (23800

I'm trying to calculate predicted probabilities in R with Zelig and keep getting the following error. Can anyone help? > x.low <- setx(mod, type=1)Error in dta[complete.cases(mf), names(dta) %in% vars, drop = FALSE] : incorrect number of dimensions When I ran the model, I ran everything but the explanatory variable as a numeric variable. Now, I'm trying everything and no

Hello, I am attempting to "automate" a Bayesian normal linear regression using Zelig. Basically, I have a list containing several zelig() objects, each having a different formula, same data set, and same model (normal.bayes). My problem lies in the setx() method, where I am setting a numeric parameter to a value other than the mean. This is straightforward if I input the parameters

Hi, When modeling with negbin from the aod package, parameters for a given count y | lambda~Poisson(lambda) with lambda following a Gamma distribution Gamma(r, theta) are estimated. The intercept is called phi. Some other parameters may be also be estimated from factors in the data: the estimates returned for all these would be in accordance with the Value listing in the negbin entry in the aod

Hi, I wonder if predict.gam is supposed to work with family=negbin() definition? It seems to me that the values returned by type="response" are far off the observed values. Here is an example output from the negbin examples: > set.seed(3) > n<-400 > dat<-gamSim(1,n=n) > g<-exp(dat$f/5) > dat$y<-rnbinom(g,size=3,mu=g) >

I have tried glm.nb in the MASS package, but many models (I have 250 models with different combinations of predictors for fish counts data) either fail to converge or even diverge. I'm attempting to use the negbin function in the AOD package, but am unsure what to use for the "random" term, which is supposed to provide a right hand formula for the overdispersion parameter.