similar to: Standardized deviance residuals in plot.lm

Hi Folks, I've got a question concerning the calculation of the Schwarz-Criterion (BIC) done by summary.regsubsets() of the leaps-package: Using regsubsets() to perform subset-selection I receive an regsubsets object that can be summarized by summary.regsubsets(). After this operation the resulting summary contains a vector of BIC-values representing models of size i=1,...,K. My problem

Dear R users, just a quick question: Is there a reliable and good graph library for R, eg. with shortest path algorithms on adjacency matrixes? I already found a graph package as part of "Bioconductor". Are there more? If anyone knows and would tell me, I appreciate very much! Cheers, Andre -- Dipl.-Inform. Andre Skusa (PhD student) NRW Graduate School in Bioinformatics and

Hi everyone, Is there a way to make R save the workspace output (just the results, not the objects themselves) as you go? I'm running analysis that takes a long time to run and I want to be able to interrupt it without losing all the output to date. Is there an alternative to putting "save.image()" commands after every couple lines of code? Best, Tatyana

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant

Dear sir, I am fitting a glm with default identity link: model<-glm(timetoacceptsecs~maleage*maletub*relweight*malemobtrue*femmobtrue) the model is overdisperesed and plot model shows a low level of linearity of the residuals. The overdispersion and linearity of residulas on the normal Q-Q plot is corrected well by using:

Dear all, my problem is following. I know Stata, but currently I have to use R. Could You please help in finding the analogy to R. (1) creating of City-Dummy. I know in Stata: g byte city=0 replace city=1 if city==12&year==2000 and (2) Create a Time-Dummy-Variable g byte T2000=0 replace T2000=1 if year==2000 (3) I need the City DUmmy for the following combination: I have the

Hello, I would like to compare two different models in the framework of Cox proportional hazards regression models. On Rsitesearch and google I don't find a clear answer to my question. My R-Code (R version 2.9.0) coxph.fit0 <- coxph(y ~ z2_ + cluster(as.factor(keys))+ strata(stratvar_), method="breslow" ,robust=T ) coxph.fit1 <- coxph(y ~ z_ +

There are a couple of points to keep in mind when doing a log-transform of an exponential model, such as -- y = a*exp(b*x) 1. The implicit statistical model is multiplicative in the error. The implied statistical model of the log transform is -- log(y) = log(a) + b*x + u which implies -- y = a*exp(b*x)*exp(u) A linear regression in the log

Hi, I've encountered a strange problem while using FreeBSD 6.0 for our local mirror (mirror.math.uni-bielefeld.de) and thus is providing access via ftp, http, rsync and cvsup (all local and remote). The system crashes periodically with a kernel panic (panic: sbdrop). The uptimes between two crashes are going from a few hours to a few weeks. The system is a i386, Intel Pentium 4 based with

Hello, I have a small problem with developing design matrix X, which I use in estimation the log-likelihood of a multinomial logit model. I have the data: number of observation - 289 number of choice alternative- 3 number of choice specific variables in matrix X -4 matrix X =289x4 I tried to use the function createX, I know that I have to get design matrix 289x12 (am I right?) but

hi list can U help me caller id in USTM if now working -- Starting switch on '4211 at 4211-1' to 4203 -- Executing [4203 at office:1] DumpChan("USTM/4211 at 4211-0x7f7ba4228fd0", "") in new stack Dumping Info For Channel: USTM/4211 at 4211-0x7f7ba4228fd0: ================================================================================ Info: Name=

Hello, I'm currently trying to implement streaming off ogg-files out of an archive file using SDL and SDL_mixer for playback. Therefore i create a FILE * filepointer, place it to the beginning of an ogg file inside the archive and hand over the filepointer to ov_open. ( command: ov_open(fp, &music->vf, NULL, 0) ). This works fine so far. The problem is: if i put many oggs together in

Hello, I have a small problem with developing design matrix X, which I use in estimation the log-likelihood of a multinomial logit model. I have the data: number of observation - 289 number of choice alternative- 3 number of choice specific variables in matrix X -4 matrix X =289x4 I tried to use the function createX, I know that I have to get design matrix 289x12 (am I right?) but

The Wine development release 1.6-rc2 is now available. What's new in this release (see below for details): - Bug fixes only, we are in code freeze. The source is available from the following locations: http://prdownloads.sourceforge.net/wine/wine-1.6-rc2.tar.bz2 http://mirrors.ibiblio.org/wine/source/1.6/wine-1.6-rc2.tar.bz2 Binary packages for various distributions will be available

A maybe trivial and stupid question: In the case of a lm or glm fit, it is quite informative (to me) to have a look to the null deviance and the residual deviance of a model. This is generally provided in the print method or the summary, eg: Null Deviance: 658.8 Residual Deviance: 507.3 and (a bit simpled minded) I like to think that the proportion of deviance 'explained' by the

Dear R users, I read your methods of extracting the variance explained by each predictor in different places. My question is: using the method you suggested, the sum of the deviance explained by all terms is not equal to the deviance explained by the full model. Could you tell me what caused such problem? > set.seed(0) > n<-400 > x1 <- runif(n, 0, 1) > ## to see problem

Hi. Sometimes I see much contention in smp_tlb_shootdown while running sysbench: sysbench --test=fileio --num-threads=8 --file-test-mode=rndrd --file-total-size=3G run kern.smp.cpus: 8 FreeBSD 7.1-R CPU: 0.8% user, 0.0% nice, 93.8% system, 0.0% interrupt, 5.4% idle Mem: 11M Active, 2873M Inact, 282M Wired, 8K Cache, 214M Buf, 765M Free Swap: 4096M Total, 4096M Free PID USERNAME PRI NICE

I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print( names( theta ) ) # returns NULL ## get the values of the parameters for( i in 1:length( theta ) )

Dear R programming folks: I'm trying to finish off a package for non-linear simultaneous system estimation and I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print(

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