similar to: Environment of a formula

Dear all, I am trying to use xyplot inside a function plotme<-function(dataframe) { xyplot(x~y|z,data=dataframe) } x,y,z are members of the data frame. When calling function library(lattice) plotme(dataframe) nothing happens. (R-1.8.0, SuSe Linux 8.1) What am I doing wrong? Many thanks in advance Peter

Could I suggest the following extension to plot.formula: plot(cbind(y1,y2) ~ x, ...) should plot (y1 against x) and (y2 against x) on the same plot. The default y axis limits would be determined by the range of c(y1,y2). This would be pretty handy sometimes, replacing 4 lines of code. The current plot.formula evaluates cbind(y1,y2), which is a matrix, so plot.formula looks for

gReetings, I want to manipulate a formula object, containing the name "." so that "." is replaced by a desired (arbitrary) expression. What is a safe way to do this? Adrian Baddeley

Can anyone suggest a simple way to calculate a 'hash code' from an arbitrary R object? hash(x) should return an integer or string with the property that if hash(x) != hash(y) then x and y are not identical and the time to compute hash(x) should be quite short. Any suggestions welcome thanks Adrian Baddeley

Sorry if this is a FAQ. Is there a good reason why a factor has to be a one-dimensional vector and cannot be a matrix? I want to construct matrices of categorical values. Vain attempts like matrix(factor(c(T,F,F,T), 2,2) yield a matrix of character strings representing the factor levels, not the levels themselves, while factor(matrix(c(T,F,F,T), 2,2)) converts the matrix to a

Dear R developers A question about the class 'listof', defined in package 'stats'. Other than its definition and use in the code for 'anova', we can't see that the class 'listof' is used for anything else (in recommended packages, or elsewhere). In the spatstat package we have been using a 'listof' to represent a list of spatial objects of the same

Dear Mr. Baddeley   I just graduated from a Masters in Applied Mathematics on Jun19th. My thesis was about spatial distribution /a nalysis of some trees in a part of  the Congo Basic Forest. In my thesis I used your spatial package in R, and today I'm doing a more deeper study about how we choise the r distance in Function F(). I would like to be able to understand about value of rmaxdefault

Greetings - Is it possible, inside .First.lib, to find out the version number of the package that is being loaded? If only one version of the package has been installed, we could scan the DESCRIPTION file, something like .First.lib <- function(lib, pkg) { library.dynam("spatstat", pkg, lib) dfile <- system.file("DESCRIPTION", package="spatstat")

Rainer M Krug writes: > Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004. > Rings, circles and null-models for point pattern analysis in ecology. > Oikos 104: 209-229 a statistic he called O-Ring statistic which is > similar to Ripley's K, only that it uses rings instead of circles. > > http://www.oesa.ufz.de/towi/towi_programita.html#ring

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

Hello, All: The vignette with the sos package used "upquote.sty", required for R Journal when it was published in 2009. Current CRAN policy disallows "upquote.sty", and I've so far not found a way to pass "R CMD check" with sos without upquote.sty. I changed sos.Rnw per an email exchange with Prof. Ripley without solving the problem; see below. The

Bug summary: glm() causes a segfault if the argument 'data' is a data frame with more than 16384 rows. Bug demonstration: -------input --------------- N <- 16400 df <- data.frame(x=runif(N, min=1,max=2),y=rpois(N, 2)) glm(y ~ x, family=poisson, data=df) ------ output --------------- *** caught segfault *** address (nil),

R-help, Given a simple linear model, say lm(x ~ y + z), I would like to remove model terms that are factors with only one level. Thus, if 'z' were a factor with only one level, lm(x ~ y + z) becomes lm(x ~ y + 1). Likewise, if both 'y' and 'z' are one-level factors, then the resulting calculation is simply lm(x ~ 1). Unfortunately, I have not been able to come up with an

Hi, all, I just recently noticed a change in terms.formula from 2.2.1 to 2.3.1 (possibly 2.3.0, but I didn't check). Here's the problem: ## 2.2.1 > update(~ x | y, z ~ .) z ~ x | y ## 2.3.1 > update(~ x | y, z ~ .) z ~ (x | y) and in the NEWS for 2.3.1 o terms.formula needed to add parentheses to formulae with terms containing '|'. (PR#8462) So, there must be

Ranjan Maitra writes: > Does anyone have a suggestion (or better still) code for sampling > from the uniform distribution over the convex hull of a set of > points? This is implemented in library 'spatstat'. If x and y are vectors of coordinates of your initial set of points, library(spatstat) W <- convexhull.xy(x, y) P <- runifpoint(42, W) will compute

Hi, Sorry if this is already known... contour() sometimes draws contour lines that intersect. Is there a temporary fix? A dataset which causes problems is at http://www.maths.uwa.edu.au/~adrian/dumpdata.R If you try just source("dumpdata.R") image(huh) contour(huh) the 100 x 100 matrix 'huh' contains an hourglass-shaped region of values around 0.8. The contour plot

After a lot of effort I developed the following function to compute the bounding ellipse (also known a as minimum volume enclosing ellipsoid) for any set of points. This script is limited to two dimensions, but I believe with minor modification the algorithm should work for 3 or more dimensions. It seems to work well (although I don't know if can be optimized to run faster) and

So thanks for the help, I have a matrix (AB) which in the first column has my bin numbers so -4 - +4 in 0.1 bin units. Then I have in the second column the frequency from some data. I have plotted them and they look roughly Gaussian. So I want to fit them/ find/optimize "mu", "sigma", and "A". So I call the nls function : nls_AB <- nls(x ~ (A/sig*sqrt(2*pi))*

Thanks to Andy Liaw and Baz for alternatives to tinkering with plot.formula to get plot(cbind(y1,y2) ~ x, ...) to work. However... > From: "Liaw, Andy" <andy_liaw at merck.com> matplot(x, cbind(y1, y2), ...) > From: Barry Rowlingson <B.Rowlingson at lancaster.ac.uk> xyplot(y1+y2~x,data=xyy,allow.multiple=T) The former requires separate code for the

A question about the inner workings of glm() and dpois(): Suppose I call glm(y ~ x, family=poisson, weights = w) where y contains NON-INTEGER (but still nonnegative) values. (a) Does glm() still correctly maximise the weighted Poisson loglikelihood ? (i.e. the function given by the same formal expression as the weighted loglikelihood of independent Poisson variables Y_i except that the