similar to: Deviance function in regression trees

Hello all, I was wondering if anyone is aware of formal approaches and tools for comparing partial response curves produced in GAM? My interest is in determining if two partial response curves are "statistically" different. I recognize that point-wise standard error estimates can be produced using the GAM package but Im not certain how to translate this into a statistical test for the

Sirs; I have read your web site page current issues and debugging and I am interested in how to debug a rsync issue which ends with the following message: io timeout after 60 seconds -- exiting rsync error: timeout in data send/receive (code 30) at io.c(181) I have compiled rsync on a hpux 11.11 server and I am using rsync-2.6.4. The remote machine is running rsync as a deamon in inetd.

I'm trying to implement a connection between two processes using a simple socket mechanism. The messages are rather long object stored as JSON. R is crashing with a segmentation fault when I try to read my test message (which is 5305 bytes long). I first send the length in bytes and then I send the actual message. Here is my R code: library(jsonlite) library(futile.logger)

Thanks for the link.? Somehow the information about how to join the bugzilla site was not available at bugzilla and buried in the CRAN web site instructions on reporting bugs (which pointed me at Bugzilla and not the page you showed me). The example is pretty minimal.? I left the tracing statements (flog.trace()) and the toJSON, fromJSON in as I thought they might provide some context for

Thanks for the report, but it is unlikely anyone would be able to help just based on this code fragment. We need a small and minimal but complete reproducible example. That example should not use any contributed packages (a contributed package may be corrupting memory, which may cause R to crash). It is easy to get a bugzilla account - please see https://www.r-project.org/bugs.html for more

I have used packages rpart, mvpart and tree for classification and regression trees. I want to calculate fraction of null deviance explained by each node and variable in the tree. For instance, at the first split, this would be (1 - (sum of residual deviance in each of the two leaves)/deviance at the root). In the subsequent splits, this formula is slightly different. There probably is a function

Hello, I have been using FreeBSD-7.0STABLE with BIND-9.4.2 ( i guess, forget to check before upgrade) up to 2008-01-26 (yesterday). But after upgrade FreeBSD-7.0STABLE-->FreeBSD-7.1STABLE everything goes wrong. 1.BIND can't start anymore and giving me following message at /var/log/messages: . . . Jan 27 12:30:20 ns kernel: ad4: 152587MB <WDC WD1600AAJS-75PSA0 05.06H05> at

From /var/log/messages: starting BIND 9.4.3-P1 -t /var/named -u bind could not get query source dispatcher (0.0.0.0#53) loading configuration: address in use exiting (due to fatal error) I had just updated from 5-stable (at 5.5) to 6-stable (at 6.4). Upon today's upgrade I got to 7.1. Everything else seems to be be working (the machine is basically a webserver), except named. apache is

Hello, Freebsd-stable. BIND on my new router (7.1-STABLE, BIND 9.4.3-P1) shows bunch of errors on every start and doesn't answer on requests for 30-60 seconds after that. Errors are like this: Jan 24 12:18:12 gateway named[1455]: /usr/src/lib/bind/isc/../../../contrib/bind9/lib/isc/unix/socket.c:1567: unexpected error: Jan 24 12:18:12 gateway named[1455]: internal_send: 193.0.14.129#53:

I'm trying to display my deciles without scientific notation, but have not found an option that will allow me to do so. According to web searches, the options(scipen=999) should remove scientific notation, but it seems not too. Does this option work with quantcut function? Is there any other option that can be used? I am using verison 2.10.0. library(gtools) library(gdata)

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 everyone, I''m currently investigating re-writing our School CMS application in Rails and the only drawback I can see is there isn''t an ample supply (if any) of WYSIWYG In-browser editors written with a raw Ruby backend. We currently use KTML4 which is written with PHP as a base. I''m interested to hear from anyone who''s integrated a PHP based editor into

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Hi Everyone, I'm working on building some classification trees, and up to this point I've been using rpart. However, I recently discovered the tree package, and found that it had some useful functions (in particular deviance(), which I would really like to use for my project). I can't seem to find an equivalent function for rpart. I've considered using tree() in place of

I'm running a categorical data analysis with a two-way design of nominal by ordinal structure like the Political Ideology Example (Table 9.5) in Agresti's book Categorical Data Analysis. The nominal variable is Method while the ordinal variable is Quality (Bad, Moderate, Good, Excellent). I rank/quantify Quality with another variable QualityR (1, 2, 3, 4), and run the following:

It seems that the standardized deviance residulas, that one gets on plots of a glm.object x with plot(x) are calculated as r <- residuals(x) s <- sqrt(deviance(x)/df.residual(x)) w <- weights(x) hii <- lm.influence(x)$hat r.w <- if (is.null(w)) r else (sqrt(w) * r) rs <- r.w/(s * sqrt(1 - hii)) This implies that, for example, for binomial B(ni,pi) data the devaince residials

Hi all, I'd like to fit different models using a loop together with the jags package. to do this, I load the following packages "runjags", "R2jags" and "coda" and use the function "jags" to fit my models. The problem is that the following a windowx with the following message appear between each model fitting inside my loop : the following objects in

Hi, I am doing a regression tree using the package 'rpart' but could not able to calculate the residual mean deviance. Please help. Narayan [[alternative HTML version deleted]]

Dear all, I would like to get glm() return its results (at least the deviance) for some given parameter values (ie without actually fitting the model). I tried to set `maxit = 0' but this does not work, eg: > glm(y ~ x, start = c(1, 1), maxit = 0) Error in glm.control(...) : maximum number of iterations must be > 0 Any idea? Thanks in advance. Emmanuel Paradis