similar to: confusion over "names" of lm.influence()$hat

Is there a routine in the boot package to get the jackknife-after- bootstrap influence values? That is, the influence values of a jackknife of the bootstrap estimates? I can see how one would go about it from the jack.after.boot code, but that routine only makes pretty pictures. It wouldn't be hard to write, but I find it hard to believe this isn't part of the package already. Thanks

Dear list members, I would like to ask two questions, although the second one must have been answered a thousand times. 1) is there a simple way to estimate the influence of individual variables in PCR and PLS models? What I have in mind is a way to rank the variables according to their influence, using some numerical value of a statistic. 2) what is the proper way to cite a CRAN package? How

Many thanks to those who replied to my message regarding installation of the lattice package. I have now upgraded my version of R. I have a quick question: I am running mixed effects models using the lme command. I am wanting to assess the fit of these models using the usual plots including Cooks Distance plots. I have noticed from the help files that it is possible to run influence measures

Hello, Is it possible to model and solve influence diagrams in R? I would appreciate your help. Pavel.

I make a regression using the lm.rigde function from library MASS. Now i want some measures of influence. Is there a way to use a lm.ridge object into the function influence.measures? -- bertola at fastmail.fm --

I am hoping that some one might be to tell me whether there are any functions that produce influence measures for lme /nlme objects (i.e those suggested by Lesaffre and Verbeke or Langford and Lewis for multilevel models). Thanks in advance. ----------------------------------------------- Anthony A. Pezzola apezzola@uc.cl (02) 354-7823 Profesor de Ciencia Política Instituto de Ciencia

Hi, I know this is the wrong forum for this kind of question and is only ephemerally related to xapian, but maybe someone here knows and will save me some digging. Given a google PR of, say, .15 for page A of site x.com, does google "radiate" any of that PR goodness onto any other pages of site x.com? Irrespective of whether page A links to any other pages in site x.com. In other

I wondered why mdbox_rotate_size is 2MB by default. I thought if I increased it to 16MB, maybe there would be less disk io, but I dont see any difference. Furthermore I read in some thread that increasing it from 2MB, could give problems when deleting messages, can someone explain this? Does anyone have this on a cephfs mount, does it make sense to set this to 4MB? [@test2 ~]# pr -m -t

(R 0.65.0 and earlier): example(aov) lm.influence(npk.aov) gives Error: NA/NaN/Inf in foreign function call (arg 6) which comes from the lm.obj$coefficients (the last 3-way interaction coefficient is indetermined and accordingly NA) argument passed to .Fortran("lminfl",...) inside lm.influence. The following is a simple correct patch --- lm.influence.R 1999/08/13

Hi all, Does lme has function to compute the cook's distance or influence measure like lm? I can't find them. Thanks. Yen Lin [[alternative HTML version deleted]]

Dear R users, I'm trying to construct a distance matrix based on a nb object created by spdep where sites must have a larger influence in one direction then in the other. Here is an example to better illustrate what I need: Let say I have the following Gabriel connection network library(spdep) library(ade4) data(orbatid) nbgab<-graph2nb(gabrielneigh(as.matrix(oribatid$xy)))

Hello, I'm plotting a data-frame and use plot(......., pch=...) as well as setting pch with par(pch=...) but always get the default symbol (circle) for the plots. Does pch have no effect, when plotting a complete data-frame, instead of certain values/vectors? How to change the behaviour? Do I have to change the print-function? TIA, Oliver

HI, Dear Greg, I have one question about the variable relative influence plot: THE following is the rel.inf value of 25 variables, but wen I plot, not all the variables are labeled. i.e. num_genes, wg, hydrophob_per etc are not labeled on the y-axis. also the variables are labeled vertically, can it be labeled horizontally just like the summary table? Thanks! > summary(gbm1,

A while back I asked about getting a list of points that R considers influential after fitting a linear model, and very quickly got a helpful pointer to influence.measures(). But "it has happened again." The trouble I am having is that points marked on plots are not flagged in the output from influence.measures(), and I can't read them on the plots. I tried some successive

I am a novice R user, and I am having difficulty understanding R's influence plots. I am trying to remove outliers from a particular variable, "sib." I am able to generate influence plots and further outlier information such as below (which is a shortened example). For my analyses, I end up excluding the points R refers to, 7, 18, 26, and 105. However, my question is, how can I

Hi dear all, I'm wondering about the question that; Does the influence.measures(model) for linear models valid for general linear models such as logistic regression models? That is; If I fit the model like model <- glm( y~X1+X2, family=binomial) Then, if i apply the function "influence.measures(model), i will get the result of influence measures. These result are valid for

Hello. I want to get the proper influence function for the glm coefficients in R. This is supposed to be inv(information)*(y-yhat)*x. So I am wondering what is the exact mathematical formula for the output that the functions: dfbeta() OR lm.influence()$coefficients return for a glm model. I am confused because: 1. Their columns don't sum to zero as influences should. 2. They

Hello everyone ! I am currently trying to convert a program from S-plus to R, and I am having some trouble with the S-plus function called "influence(data, statistic,...)". This function aims to "calculate empirical influence values and related quantities", and is part of the Resample library that I cannot find for R. However, 2 similar functions are available in R: - the

Dear list, I've noticed that influence.measures and cooks.distance gives different results for non-gaussian GLMs. For example, using R-1.9.0 alpha (2003-03-17) under Windows: > ## Dobson (1990) Page 93: Randomized Controlled Trial : > counts <- c(18,17,15,20,10,20,25,13,12) > outcome <- gl(3,1,9) > treatment <- gl(3,3) > glm.D93 <- glm(counts ~ outcome +

Hi all I share my Asterisk Server with a few friends. It is connected to PSTN, and various SIP Providers. I offer Free Calls to my friends, but myself I would like to be able to make calls to non free destinations via my PSTN Line. Now I do this in my dialplan: ----------------------- [myself] ; National Destinations exten => _0z.,1,Dial(SIP/someisp/${EXTEN}); exten =>