similar to: extracting characteristics of datasets from data()

[Env: R 2.12.2, WinXp] In a vignette for the vcdExtra package, I had a text file, tv.dat under data/, that I used in the vignette as <<tv1,results=verbatim>>= tv.data<-read.table(system.file("data","tv.dat",package="vcdExtra")) head(tv.data,5) @ I was told that this now generates a warning for non-Rdata files in R CMD check. But I'm now

I received the following email note re: the vcdExtra package > A vcd update has shown that packages TIMP and vcdExtra are not > declaring their dependence on colorspace/MASS: see > > http://cran.r-project.org/web/checks/check_results_vcdExtra.html But, I can't see what to do to avoid this, nor understand what has changed in R devel. Sure enough, CRAN now reports errors in

Dear List, I am looking to perform exploratory analyses of two (relatively) large datasets of categorical data. The first one is a binary 80x100 matrix, in the form: matrix(sample(c(0,1),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c( "group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "V.3",

I have a print method for a set of statistical tests, vcdExtra::CMHtest, for which I'd like to have more sensible printing of pvalues, as in print.anova(). [Testing this requires the latest version of vcdExtra, from R-Forge **|install.packages("vcdExtra", repos="http://R-Forge.R-project.org")|** ] With my current print method, I get results like this, but all Prob values

In the vcdExtra package on R-Forge, I have functions and generic methods for calculating log odds ratios for R x C x strata tables. I'd like to define methods for fitting weighted lm()s to the resulting loddsratio objects, but I'm having problems figuring out how to do this generally. # install.packages("vcdExtra", repos="http://R-Forge.R-Project.org")

[Env: R 2.11.1, Win Xp, using Eclipse/StatET] In a package I'm working on, I want to create as.matrix() and as.array() methods for a particular kind of object (log odds ratios). These are returned in a loddsratio object as the $coefficients component, a vector, but really reflect an underlying (R-1)x(C-1)xstrata array, whose attributes are contained in other components. I define coef,

For the vcdExtra package, I'm exploring methods to generate and fit collections of glm models, and handling lists of such model objects, of class "glmlist". The simplest example is fitting all k-way models, from k=0 (null model) to the model with the highest-order interaction. I'm having trouble writing a function, Kway (below) to do what is done in the example below >

[Sorry if duplicate, one earlier was corrupt] Hi, I got section mismatches reported by modpost in latest build. It got reported for xen_register_pirq and xen_unplug_emulated_devices functions. xen_register_pirq makes reference to acpi_sci_override_gsi in init.data section; marking xen_register_pirq with __init is not feasible since calls are made to it from

[Sorry if duplicate, one earlier was corrupt] Hi, I got section mismatches reported by modpost in latest build. It got reported for xen_register_pirq and xen_unplug_emulated_devices functions. xen_register_pirq makes reference to acpi_sci_override_gsi in init.data section; marking xen_register_pirq with __init is not feasible since calls are made to it from

[Sorry if duplicate, one earlier was corrupt] Hi, I got section mismatches reported by modpost in latest build. It got reported for xen_register_pirq and xen_unplug_emulated_devices functions. xen_register_pirq makes reference to acpi_sci_override_gsi in init.data section; marking xen_register_pirq with __init is not feasible since calls are made to it from

With ggplot2, I can plot the glm stat_smooth for binomial data when the response is binary or a two-level factor as follows: data("Donner", package="vcdExtra") ggplot(Donner, aes(age, survived)) + geom_point(position = position_jitter(height = 0.02, width = 0)) + stat_smooth(method = "glm", family = binomial, formula = y ~ x, alpha = 0.2, size=2) But how can I

Feliz año a todos! Y al que sepa y tenga tiempo, una duda: Quiero hacer un análisis de distribución de léxico (supongo que da igual eso) mediante mosaicplot(), en particular me interesa que me muestre el peso de la distribución según una proporción que ya conseguí sacar; la de el uso de x termino en un espacio determinado. Ejemplo: Distribución de los términos, totales (tabla1) sitio1

I'm checking a new release of vcdExtra via win builder with R-devel 2014-10-29 r66897 and have run into a Warning I don't know how to fix. I have one S3 generic, mosaic3d() that uses rgl and don't want to have rgl always loaded via Depends:. Instead, the mosaic3d.default() method includes if (!require(rgl)) stop("rgl is required") This always worked in the past, but

In checking my vcdExtra package, the following NOTE newly appeared (R-Forge, using R version 3.0.1 Patched (2013-08-20 r63635)) Package in Depends field not imported from: ?gnm? These packages needs to imported from for the case when this namespace is loaded but not attached. In the DESCRIPTION file, I have Depends: R (>= 2.10), vcd, gnm (>= 1.0.3) In NAMESPACE: # we are a vcd

On 08/13/2017 05:18 AM, ken wrote: > Also, cowboys scoff, but I always wear a grounded wrist strap when > handling electronics. It's a good idea, especially in low-humidity climates. Also noteworthy: the air moving through a hose can cause a vacuum's hose or attachment to build up a static charge, which is another reason it can be a bad idea to use a vacuum in a computer.

I posted on this topic to r-help, but never got a sufficient answer, so I'm reposting here. [Env: R 2.11.1, Win Xp, using Eclipse/StatET] In a package I'm working on, I want to create as.matrix() and as.array() methods for a particular kind of object (log odds ratios). These are returned in a loddsratio object as the $coefficients component, a vector, but really reflect an underlying

Context: I have two or more rgl-based views of a given data set, perhaps fitting different models, or showing different things across views. I want to be able to hand-rotate, zoom, scale one view to something I like, and then show the other views with matching viewpoints and scaling. so that one could flip back/forth among graphs and see only the relevant differences. In 2D, all this usually

Hi all, anyone has an idea how I could fix this? \donttest{ ## Set colors from colorspace package with a fallback col <- try(colorspace::rainbow_hcl(5), silent = TRUE) %||% rainbow(5) } The problem is that this makes R CMD check freak out (http://www.r-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/falsy-00check.html) if the colorspace package is not declared as a dependency.

Dear R gurus, I am looking for a way to fit a predictive model for a contingency table which has counts. I found that glm( family=poisson) is very good for figuring out which of several alternative models I should select. But once I select a model it is hard to present and interpret it, especially when it has interactions, because everything is done "relative to reference cell". This

Hello: What is the most efficient way to change the plotted variable names in mosaic plots in the vcd package? Should one do a separate contingency table first, change the dimension names there and then pass that to mosaic? Or is there a way to do it simply within mosaic. I was thinking something like: mosaic(~var1+var2, labelling_args=list(varnames=c('newvar1', 'newvar2')) Simon