similar to: glm deviance question

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:

Running a binary logit model on the data df <- data.frame(y=sample(letters[1:3], 100, repl=T), x=rnorm(100)) reveals some residual deviance: summary(glm(y ~ ., data=df, family=binomial("logit"))) However, running a multinomial model on that data (multinom, nnet) reveals a residual deviance: summary(multinom(y ~ ., data=df)) On page 203, the MASS book says that "here the

Hi: I'm working with multinomial models with library nnet, and I'm trying to get the explained deviance (pseudo R^2) of my models. I am assuming that: pseudo R^2= 1 - dev(model) / dev (null) where dev(model) is the deviance for the fitted model and dev(null) is the deviance for the null model (with the intercept only). library(nnet) full.model<- multinom(cbind(factor1,

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

Dear all, I'm trying to fit a statistical model to series of measurements. Unfortunately, my knowledge of statistics is rather limited, so I'm a bit at loss of what is going on with the model. First of all, I've prepared a histogram. Then, I've tried to fit a Poisson model to express the relation between the middle points of classes (mids) and the corresponding frequencies

Dear R-users, To obtain the percentage of deviance explained when fitting a gam model using the mgcv library is straightforward: summary(object.gam) $dev.expl or alternatively, using the deviance (deviance(object.gam)) of the null and the fitted models, and then using 1 minus the quotient of deviances. However, when a gamm (generalizad aditive mixed model) is fitted, the

Dear list, I'm wondering if anyone can help me calculate the deviance of either a zeroinfl or hurdle model from package pscl? Even if someone could point me to the correct formula for calculating the deviance, I could do the rest on my own. I am trying to calculate a pseudo-R-squared measure based on the R^{2}_{DEV} of [1], so I need to be able to calculate the deviance of the full and null

I'm fitting glm models and the summary gives the deviance of the model . I would like to obtain the log likelihood How can I do ? Thanks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not

I am in the process of setting up R1.3.1 on a new computer running windows 2000. I am having problems running the PFE text editor simultaneously within R for editing functions and outside R for editing ordinary text files. The PFE editor behaves as I expected, if it is opened in R AND but no other PFE window is open outside R. Similarly, it also works fine if I am editing a text file outside

Dear all, I've replicated the cheese tasting example on p175 of GLM's by McCullagh and Nelder. This is a 4 treatment (rows) by 9 ordinal response (cols) table. Here's my simple code: #### cheese library(MASS) options(contrasts = c("contr.treatment", "contr.poly")) y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,7,

Could someone please point me to a source for the archives of this news group after June 21. I was subscribed to a digest version, but it stopped arriving after that date. Anne ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Anne E. York National Marine Mammal Laboratory Seattle WA 98115-0070 USA e-mail: anne.york at noaa.gov Voice: +1 206-526-4039 Fax: +1 206-526-6615

dum is a simple data frame transferred to Splus using the dump() command in Splus and the source() in R. All fields are numeric. There are no missing data. The data frame looks like it is should: > apply(dum,2,mode) yrcl sland s02 s234 "numeric" "numeric" "numeric" "numeric" > apply(dum,2,is.vector) yrcl sland s02 s234

Hello I have a problem when fitting a mixed generalised linear model with the lmer-function in the Matrix package, version 0.98-7. I have a respons variable (sfox) that is 1 or 0, whether a roe deer fawn is killed or not by red fox. This is expected to be related to e.g. the density of red fox (roefoxratio) or other variables. In addition, we account for family effects by adding the mother

Here is a simple example of what I would like to do: Given a data frame foo with variables x and fn. Suppose fn is a vector of characters which correspond to names of previously defined functions which have only one argument. I would like a vector returned where fn is applied to x foo <- data.frame(x=c(2,5,7), fn = letters[c(6,7,6)]) foo$fn <- as.character(foo$fn) "f" <-

Dear R-help, I find the example() function is extremely useful in many ways. However, there's a minor inconvenience: for long examples, it leaves lots of objects in the workspace. While it's sometimes useful to have the objects around for further exploration, other times they just add to the clutter. Does anyone have a good way of cleaning up afterward? If not, would R core consider

Could someone suggest a mail reader that will parse a digest from r-help into separate messages? Preferably, this reader would allow replies or forwards of separate messages. I use pine on a Sun running SunOS 5.7. If there were an add-on to pine that would accomplish this task, that would be even better. Anne ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Anne E. York National Marine Mammal Laboratory

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

Anyone see any reason not to add these extra compiler/linker flags if they're supported? Index: aclocal.m4 =================================================================== RCS file: /home/dtucker/openssh/cvs/openssh/aclocal.m4,v retrieving revision 1.8 diff -u -p -r1.8 aclocal.m4 --- aclocal.m4 20 May 2011 01:45:25 -0000 1.8 +++ aclocal.m4 17 Dec 2012 03:56:32 -0000 @@ -21,6 +21,23 @@

I've been trying to download from CRAN the floppy versions of the R source files: R-release-1.tar.gz, R-release-2.tar.gz I tried the servers in Seattle, Madison, and the Vienna Technical University. In each case, the file(s) were unavailable. Anne ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Anne E. York National Marine Mammal Laboratory Seattle WA 98115-0070 USA e-mail: anne.york at noaa.gov

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