similar to: negetative AIC values: How to compare models with negative AIC's

Dear R-list, *When comparing two logistic regression models with the anova CHi test, I obtain the following error: (there are no NA's in the time series). How can this be solved such that I can compare two models on the same dataset were different explanatory variables are used? l.KBDI <- glm(zna.arson2 ~ zna.KBDI,family = binomial) l.NDWI <- glm(zna.arson2 ~ zna.NDWI,family

Dear R list, From the lrm() binary logistic model we derived the G2 value or the likelihood-ratio chi-squared statistic given as L.R. model, in the output of the lrm(). How can this value be penalized for non-linearity (we used splines in the lrm function)? lrm.iRVI <- lrm(arson ~ rcs(iRVI,5), penalty=list(simple=10,nonlinear=100,nonlinear.interaction=4)) This didn’t work

Dear R helpers, >From the lrm( ) model used for binary logistic regression, we used the L.R. model value (or the G2 value, likelihood-ratio chi-squared statistic) to evaluate the goodness-of-fit of the models. The model with the lowest G2 value consequently, has the best performance and the highest accuracy. However our model includes rsc() functions to account for non-linearity. We

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Hi I want astackedBar graph in my project I want to give it negetive axis, scale, negetive values etc . How can I do that with gruff package? Thanks.. Sainaba -- Posted via http://www.ruby-forum.com/.

Is this a bug somewhere? The format function, using a specific number of digits, doesn't give sensible results: R> set.seed(2);print(x<-rexp(5)) [1] 1.86535 0.40475 0.14665 1.73071 0.08953 R> format(x,digits=1) [1] "1.87" "0.40" "0.15" "1.73" "0.09" R> format(x,digits=2) [1] "1.87" "0.40" "0.15"

Hello, We use drc to fit dose-response curves, recently we discovered that there are quite different standard error values returned for the same dataset depending on the drc-version / R-version that was used (not clear which factor is important) On R 2.9.0 using drc_1.6-3 we get an IC50 of 1.27447 and a standard error on the IC50 of 0.43540 Whereas on R 2.7.0 using drc_1.4-2 the IC50 is

Hi, I'm attempting to add a "Julian Day" column to a data frame. Here is my code and the resulting data frame: vic.data <- read.table("C:/VIC/data/vic.data.csv", header=F) names(vic.data) <- c("year", "month", "day", "precip", "evap", "runoff", "baseflow", "Tsup",

I have these questions: (1) Use Poisson regression to estimate the main effects of car, age, and dist (each treated as categorical and modelled using indicator variables) and interaction terms. (2) It was determined by one study that all the interactions were unimportant and decided that age and car could be treated as though they were continuous variables. Fit a model incorporating these

Hello I have experienced some problems with vcut (media-sound/vorbis-tools-1.0-r1 package from Gentoo/Linux). I have a long live record I have encoded in OGG (maybe it would have been easier to cut the WAV file and encode the parts, but still). The file was encoded with oggenc from the same package as vcut. I have therefore tried to use vcut to split the long OGG file in several smaller files.

Hi All. I've had this problem with rsync, the solution to which has been really evasive to me. Any help would be appreciated. I'm running rsync 2.5.5 between 2 SCO boxes and get random "unexpected tag" errors. Sometimes the unexpected tag is positive, other times negetive, and a retry of rsync usually manages to work the second or third time round. The disks are identical in

Hello everyone, I wanted to ask if there is an R-package to fit the following Poisson regression model log(\lambda_{ijk}) = \phi_{i} + \alpha_{j} + \beta_{k} i=1,\cdots,N (subjects) j=0,1 (two levels) k=0,1 (two levels) treating the \phi_{i} as nuinsance parameters. Thank you very much -- -Tony [[alternative HTML version deleted]]

Full_Name: Madeleine Yeh Version: 1.9.1 OS: AIX 5.2 Submission from: (NULL) (151.121.225.1) After compiling R-1.9.1 on AIX 5.2 using the IBM cc compiler, I ran the checks. One of them failed. Here is the output from running the check solo. root@svweb:/fsapps/test/build/R/1.9.1/R-1.9.1/tests/Examples: ># ../../bin/R --vanilla < stats-Ex.R R : Copyright 2004, The R

In virtualized environment there are mainly three problems related to spinlocks that affects performance. 1. LHP (lock holder preemption) 2. Lock Waiter Preemption (LWP) 3. Starvation/fairness Though Ticketlocks solve fairness problem it worsens LWP, LHP problems. Though pv-ticketlocks tried to address these problems we can further improve at the cost of relaxed fairness. The following patch

In virtualized environment there are mainly three problems related to spinlocks that affects performance. 1. LHP (lock holder preemption) 2. Lock Waiter Preemption (LWP) 3. Starvation/fairness Though Ticketlocks solve fairness problem it worsens LWP, LHP problems. Though pv-ticketlocks tried to address these problems we can further improve at the cost of relaxed fairness. The following patch

Dear All, I am using swfdec-0.8.4 player over directfb.. I am able to play stored swf files where as im not able to play any only swf files I get following error open http://www.foo.com/foobar.swf failure, err = No such file or directory Thanks and regards Deepak -------------- next part -------------- An HTML attachment was scrubbed... URL:

In virtualized environment there are mainly three problems related to spinlocks that affect performance. 1. LHP (lock holder preemption) 2. Lock Waiter Preemption (LWP) 3. Starvation/fairness Though ticketlocks solve the fairness problem, it worsens LWP, LHP problems. pv-ticketlocks tried to address this. But we can further improve at the cost of relaxed fairness. In this patch, we form a batch

In virtualized environment there are mainly three problems related to spinlocks that affect performance. 1. LHP (lock holder preemption) 2. Lock Waiter Preemption (LWP) 3. Starvation/fairness Though ticketlocks solve the fairness problem, it worsens LWP, LHP problems. pv-ticketlocks tried to address this. But we can further improve at the cost of relaxed fairness. In this patch, we form a batch