search for: correponds

Hi! I need to run ols regressions with Huber-White sandwich estimators and the correponding standard errors, without an intercept. What I'm trying to do is create an ols object and then use the robcov() function, on the order of: f <- ols(depvar ~ ind1 + ind2, x=TRUE) robcov(f) However, when I go f <- ols(depvar ~ ind1 + ind2 -1, x=TRUE) I get the following error: Error in

Dear friends, In S-PLUS, we can use the following argument, but not in R. mode12 <- gam(score1 ~ lo(latitude) + lo(longitude)) I searched the help in S-PLUS, it says lo() Allows the user to specify a Loess fit in a GAM formula, but i didn't find the correponding function in R. Anybody knows how to do the similar task in R? Thanks very much. -- With Kind Regards, oooO:::::::::

Hi, This is an easy question, however I cannot remember the exact command of doing it :-( Say I have a matrix: > ff [,1] [,2] [1,] 0.1000000 116.76987 [2,] 0.6444444 108.26811 [3,] 1.1888889 95.00240 [4,] 1.7333333 112.13647 [5,] 2.2777778 107.39893 [6,] 2.8222222 115.34615 [7,] 3.3666667 97.81029 [8,] 3.9111111 105.35119 [9,] 4.4555556

Dear List, Does anyone know how to simulate data from a GLM object correponding to values of the independent (x) variable that do not occur in the original dataset? I have tried using simulate(), but it generates a new value of the dependent variable corresponding to each of the original x-values, which is not what I need. Ideally I whould like to simulate new values for GLM objects

Dear All Sorry for this simple question, I could not solve it by spending days. My data looks like this: # data set.seed(1234) clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100 level for this factor var; yvar <- rnorm(40, 10,6); var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2); var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15,

Hi everybody! Anybody knows how can I get detalied information about clusters after using hclust? The issue is that if I have some items in different clusters, I would like to get the cluster where each item is placed. Taking into account that my data set is too large, it is not useful to have the dendogram or a graphic, and really I need something like a simple table with item label and cluster

In a dual server configuration one of the two servers fail with: WARNING[3705]: res_crypto.c:335 __ast_sign_bin: RSA Signature (key sintel-voip) failed NOTICE[3705]: chan_iax2.c:5187 authenticate: Unable to sign challenge withy key WARNING[3705]: chan_iax2.c:7191 socket_read: I don't know how to authenticate sintel-user to 10.27.33.1 We use the rsa authenticatio: in the server A

Hello people, I''m using squeegy fleximage for my site right now and having some difficulty to achieve some things. Updates photos are saved in created at date generated fom like : '' /images/2008/05/14/22.png '' . However this route is not accessible through the browser and I don''t know how to add it in my routes.rb knowing that the dates will change everyday.

Thanks for your advice. I am not sure that I understood your comment "If you need something, there should be a __builtin that corresponds to the intrinsic." Is that a better way to define an intrinsic function in C? How do you do it? I am actually trying to add several intrinsic functions for my target machine so I am looking for a simple and workable way of doing it. Thanks again.

Hi I'm using the "image" function to produce a plot and I want to define the breaks using "cut" and the colors using "heat.colors". > image(interp(mat2[,2],mat2[,1],mat2[,3]),breaks=cut(mat2[,3],30),col=heat.colors(29)) Error in image.default(interp(mat2[, 2], mat2[, 1], mat2[, 3]), breaks = cut(mat2[, : must have one more break than colour The

Greetings, I am new to R and have been comparing CPH survival analysis hazard ratios between R and SAS PhReg. The binary covariates' HRs are the same, however the continuous variables, for example age, have quite different HRs although in the same direction. SAS PhReg produces HRs which are the change in risk for every one increment change in the independent variable. How do I

I am trying to model a clusterd ordinal response data (either 1, 2 or 3) called , the correponding physician of the patient is also in the data. Since it is ordinal, I used the ordinal logit model topbox[i]~discrete with probability P[j,1],p[j,2], p[j,3], j is the corresponding physician of the ith patient C[j] is the physician effect , a1 and a1+theta is the common cutpoints for all

I tried thinning of the mcmc run with 500,000 iteration. It looks like 100 or 200 is enough to remove the autocorrelation of a1 and tau. Is that too much thining? --- On Tue, 3/16/10, ping chen <chen1984612 at yahoo.com.cn> wrote: > From: ping chen <chen1984612 at yahoo.com.cn> > Subject: an ordinal regression MCMC run high correlation > To: r-help at r-project.org >

Hello! How can one select outgoing MSN when dialing out from ttyI-interfaces? I have successfully done this with CAPI e.g... exten => _XXXXX.,2,Dial,CAPI/60:bBYEXTENSION ...in extensions.conf. Currently correponding for my ISDN modem interface is... exten => _XXXXX.,2,Dial(Modem/g1:${EXTEN}) ...but this selects only MSN of outgoing group g1 for dialout MSN number. I also tried to

Hi, First of all, my apologies for the extension of this message, but it is needeed for you to undertand my problem. Straight to the point: i have this domain in my company running in Samba 3.0.2 My users are: hcoelho, jardim, gamito, yesenia, smatias, fqueiros, faugusto, vamaro, peixinho, aragao, dina, pinho. I have this shares with the users that can access them and the correponding Linux

Hello. Id like you to help me with something here, i m trying to create a log manager just for fun but I cant make it work since the beginning. I created my project, configured the db, initialized my model Log and then my controller Log, then im just trying to use scaffold :log for the controller but I cant make it work, the error says: undefined method `errors'' for

Hi all, How can I overcome the error "object of type 'closure' not subsettable" I ran the following script seq <- paste(seq(1914, 1916, by=1), "*.y", sep=".") # make sequence c <- 3 # total number of files d2 <- file # creates dummy file # Input sequence in loop for (i in 1:3){ list <- list.files("~/ukcp09/txt/x.djf", seq[[i]]) file

Hello, Does anybody know if the outscale option of randomForest yields the standarized version of the outlier measure for each case? or the results are only the raw values. Also I have notice that this measure presents very high variability. I mean if I repeat the experiment I am getting very different values for this measure and it is hard to flag the outliers. This does not happen with two other

Dear R-users Coming from a proc mixed (SAS) background I am trying to get into the use of (n)lme. In this connection, I have some (presumably stupid) questions which I am sure someone out there can answer: 1) With proc mixed it is easy to get a hold on the estimated variance parameters as they can be put out into a SAS data set. How do I do the same with lme-objects? For example, I can see the

Hello. I'm having trouble installing rgl. I have a theory as to the problem. First, the error message and session info. > install.packages("rgl") trying URL 'http://probability.ca/cran/src/contrib/rgl_0.81.tar.gz' Content type 'application/x-gzip' length 1636939 bytes (1.6 Mb) opened URL ================================================== downloaded 1.6 Mb *