similar to: Missing values in glm

Dear all, I have a SuSE9.1 box running as a file server with mp3's on it. The /var/log/messages log file is recording the following errors which I don't understand and perhaps you could assist me: Nov 17 11:25:05 mp3-nrg smbd[7903]: [2004/11/17 11:25:05, 0] lib/util_sock.c:get_peer_addr(975) Nov 17 11:25:05 mp3-nrg smbd[7903]: getpeername failed. Error was Transport endpoint is not

I imitated predict.glm, my thing worked, now I need to revise. It would help me very much if someone would explain predict.glm line 28, which says object$na.action <- NULL # kill this for predict.lm calls I want to know 1) why does it set the object$na.action to NULL 2) what does the comment after mean? Maybe I need a pass by value lesson too, because I can't see how changing that

Maybe a useful addition to the predict functions would be to return the values of the predictor variables. It just (unless there are problems) requires an extra line. I have inserted an example below. "predict.glm" <- function (object, newdata = NULL, type = c("link", "response", "terms"), se.fit = FALSE,

Hello, everybody. I recognize I'm asking you to deal with a not-very-important problem. But its important to me :) I've noticed a little inconsistency in the print.function() output. I traced the matter to deparse.c, for which I attach a patch that addresses 3 separate things. There's one important thing that I'm willing to stand behind and 2 litter things that I think would be

Hello all, I wish to compute site scores using PCA (prcomp) on a matrix with missing values, for example: Drain Slope OrgL a 4 1 NA b 2.5 39 6 c 6 8 45 d 3 9 12 e 3 16 4 ... Where a,b... are sites. The command > pca<-prcomp(~ Drain + Slope + OrgL, data = t, center = TRUE, scale = TRUE, na.action=na.exclude) works great, and from

Dear all, I have a series of variables that looks roughly like the sample data below and I'm trying to conduct a factor analysis. I've omitted cases with missing values for the factor analysis, but now I'd like to use the scores on each component as new variables in the *original* data set for analysis. That is, I'd like to take the scores on each of the two factors and see how

Hello, I have a C++ code for 2D random walks with traps and I want to convert it in a R code with its syntaxs, can anyone help??????? It's easy for me to adapt the body but I want help with the beginig (variable declaration) and th end exporting the output to a file ( like write.table() or sink() ) Thank you... #include <iostream> #include <math.h>#include

Hi Marcello, Actually, we were careful to avoid the undefined behaviour here. In fact, we are specifically running a clang test detecting undefined behaviour. If you look at the silk_SMLABB_ovflw() macro, you will see it is based on silk_ADD32_ovflw(), which is defined as: #define silk_ADD32_ovflw(a, b) ((opus_int32)((opus_uint32)(a) + (opus_uint32)(b))) By casting to unsigned, all the cases

I have a TrippLite SmartPro UP (SMART3000RM2U) that shipped with the DB9 cable# 73-0866. nut doesn't recognize the UPS using the tripplite driver. I found this page: http://www.tripplite.com/support/download/PA12/help/device.htm The link lists the SmartPro series as using the cables 73-0724 or 73-0844 and the Internet 350/525 is listed as using a cable 73-0866. I have a few 73-0844s

--- src/opus_demo.c | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/src/opus_demo.c b/src/opus_demo.c index 72506b5..5a75679 100644 --- a/src/opus_demo.c +++ b/src/opus_demo.c @@ -245,14 +245,14 @@ int main(int argc, char *argv[]) double bits=0.0, bits_max=0.0, bits_act=0.0, bits2=0.0, nrg; double tot_samples=0; opus_uint64 tot_in, tot_out; - int

I would like to predict a matrix containing missing values according to a fitted linear model. The predicted values must have the same length as the number of observations in newdata, where missing predicted values (due to missing explanatory values) are replaced by NA. How can I achieve this? I tried the following example: > x <- matrix(rnorm(100), ncol=10) > beta <- rep(1, 10) >

Hi Jean-Marc, well spotted! The patch provided fixes the issue for me. Nevertheless, in my code (and I would suggest doing the same in libopus) I am going to replace the function with one that accumulates on 64 bits and then calculates the shift, for at least 4 reasons: - It is less and simpler code - The result is likely to be slightly more accurate in case big numbers come early in the

x <- NA na.act <- na.action(na.exclude(x)) y <- rep(0,0) naresid(na.act,y) ... currently produces the result... numeric(0) ... whereas the documentation might lead you to expect NA The behaviour is caused by the line if (length(x) == 0L) return(x) in `stats:::naresid.exclude'. Removing this line results in the behaviour I'd expected in the above example (and in a

Right, there shouldn't be a problem with undefined behavior. That said, a 64 bit implementation will work very well - in fact that's how it was done originally. The reason for the current implementation is to minimize 64-bit operations in order to improve performance on limited-width architectures. This functions gets used extensively, and I think the current implementation is faster on

Hi, I'm wondering if anyone has had experience with using RPCS printer drivers in a P&P printer share. Installing the driver onto samba went without a problem (followed the Samba howto "chapter 21: Add Printer Wizard Driver Installation") but after that, every time i try to access the printer properties it takes sometimes minutes to open or just doesn't come up at all (same

I'm wondering whether anyone has any insight into why the 'simulate' methods for the built-in glm() families (binomial, Poisson, Gamma ...) extract the prior weights using object$prior.weights rather than weights(object,"prior") ? At first I thought this was so that things work correctly when e.g. subset= and na.action=na.exclude are used. However, the current versions of

Dear all, To modelize the abundance of fish (4 classes) with a set of environmental variables, I used the polr and predict.polr functions. I would like to know how to bring the cumulated probabilities back to a discrete ordinal scale. For the moment I used the predict.polr function with the argument "class". Is there an other way? polrf <- polrf <- polr_mod(formula =

Dear "forge", > I can't access http://www-nrg.ee.lbl.gov/bro.html. What happens when you try? Is it possible you had a typo in the name? I just cut-and-paste from what you wrote above and it worked fine for me. If you send the IP address you're coming from, I can check it against LBL's Bro logs (ironically :-) and see just what's happening to your session. Vern

Hi, I want to automate a set of scripts that spit out data that are later used by R to plot graphs. However, I need to get into R's environment now and then use my R script using the source command. Is there a way to run the R script from the unix prompt ?. Thanks, Krishnan. ----------------------------------------------------------- Sivaramakrishna Iyer Krishnan (Anand) Research Assistant

Hi, I want to do a simple backup of my maildir. I read here that maildirlock is not to count on in the future and the recommended option was to use doveadm backup. However, it seems that this requires to setup another dovecot server. My questions are: - How much to I need to configure this new server? Do I need to setup user by user, or even install postfix (that's where my users are