similar to: xYplot, lmline and abline

Hi All, I need to sample a vector ("old"), with replacement, up to the point where my vector of samples ("new") sums to a predefined value ("target"), shortening the last sample if necessary so that the total sum ("newsum") of the samples matches the predefined value. While I can easily do this with a "while" loop (see below for example

Dear All, I am hoping to implement a barchart using trellis graphics where all elements have a line width of 2. Using trellis.par.set(), I am able to make most elements lwd=2, but not all. In particular, the top of the box (above the upper most strip) and the left y-axis remain one point. Code with a barchart() example is below. Any advice would be greatly appreciated. Thanks for your

Dear R-Helpers, Can anyone please help me to interpret warning messages from zeroinfl (package pscl) while fitting a zero inflated negative binomial model? The console reports convergence and the parameters seam reasonable, but these <<Warning messages: 1: algorithm did not converge in: glm.fit(X, Y, family = poisson()) 2: fitted rates numerically 0 occurred in: glm.fit(X, Y, family =

# Hi All, # # I need to solve a somewhat complex equation at many parameter values for # a number of different parameters. # A simplified version of the equation is: 0= (d1/(h1^2))-(h2*(d2^2)) # I'd like to solve it across a parameter space of d1 and d2, holding # h1 and h2 constant. # It seems that uniroot() can do it, but I don't see how to vectorize it. #

Hi All, convhulln {geometry} computes the convex hull of a set of points in n- dimensions via .call, returning the hull itself, and also "unavoidably generates a diagnostic report on an Rterm console." See the example below. I need to access the results of the diagnostic report (specifically the computed hull volume) from within R, but I cannot see how. I've looked at

Hi, I am trying to produce an xyplot with a regression line. The data should be represented as log/log but when I fit the lmline I receive an error message - the plot is fine without the log transformation, but the then the plot is meaningless. I know it must be something simple, but I just can't see it. Hope someone can help... Thanks. xyplot(log(Pk)~log(k),data=rwpk,cex=1,

Dear Sebastian Luque (and All R Users) With the following code I managed to plot different characters and regression lines for panels 2 ("Day of year 101") and >4 ("Days of year" 151, 157 and 172): xyplot(log(no.larvae)~age.cls|factor(day),data=mortal, layout=c(7,1),aspect=5/3, xlab="Age class (d)",ylab="Ln(Abundance)",

Dear All, I'm confortable with xyplot(...) and panel.lmline(...) statements (at least I thought I did :). I've used the following code to plot the decline in log-abundance of fish larvae (no.larvae) with age (age.cls, 4 to 27 days-old) for specific dates of sampling (day, 9 dates). I further plotted data with different colors and regression lines for ages 5-14 d and 17-23 d in a 7-by-1

I am wanting to generate panels showing scatterplots with the linear fitted line for two groups within each panel superimposed. I have two conditioning factors, "variable" and "Group" and I want separate panels for each level of "variable" with different symbols and "lmline"s for each level of "Group". However all observations for a group are

Hi, is it possible to reverse the order in which panel.lmline() or panel.smooth() operation in xyplot() ? This type of situation might occur when plotting some variable with depth, but the relation we want to describe is variable ~ depth, and not depth ~ variable, as the plotting formula would suggest. # an example: d <- 1:100 v <- d * rnorm(100) xyplot(d ~ v, ylim=c(100,0),

panel.lmline returns intercept and slope of y ~ x subsetted to the combination of conditioning factors given to xyplot in lattice. for instance: xyplot(Xvalues ~ log(Qvalues)|Tfac, data = df7, panel = panel.lmline) I am looking to find the equivalent formulation for lm() proper. If I do this: lmcal <- lm(Xvalues ~ log(Qvalues):Tfac, data = df7) Only one value of the intercept is returned.

Hi R Folks... Are the results of a fit carried out by panel.lmline readily available for use in a lattice plot? I¹d like to put r^2, m, and b on each panel. I can certainly write something that does this manually and then use it with panel.text, but if it¹s already available, that would be preferable, especially as lattice permits condition and subsetting so readily. Looking at panel.abline, I

In the HistData package, I have a data frame, PearsonLee, containing observations on heights of parent and child, in weighted form: library(HistData) > str(PearsonLee) 'data.frame': 746 obs. of 6 variables: $ child : num 59.5 59.5 59.5 60.5 60.5 61.5 61.5 61.5 61.5 61.5 ... $ parent : num 62.5 63.5 64.5 62.5 66.5 59.5 60.5 62.5 63.5 64.5 ... $ frequency: num 0.5 0.5

On Friday 17 September 2004 13:52, RenE J.V. Bertin wrote: > Hello again, > > I am doing regressions (using panel.lmline() (and panel.abline( > rlm(...))) ) inside a panel method which I pass to bwplot(). > > What I would like to do is create a boxplot of categorised data > (binned on the independent variable), and superpose a regression line > which is calculated using the

Hi All, I am writing a simulation that examines the effects of species extinctions on ecological communties by sequentially removing individuals of a given species (sometimes using weighted probabilities) and replacing the lost individuals with species identities randomly sampled from the remaining individuals. Thus I use two dataframes. One contains all the individuals and their species

1) I have a data that includes some "bad" data. I want to make a trellis plot where each panel contains a) A scatter plot of the "good" data b) A scatter plot of the "bad" data in a different color c) A best fit line of all the data, and d) A best fit line of the "good" data. I tried using xyplot and setting the "group" argument, but I'm

Hi, Could you help me to install the rgl package on Solaris 10 x86? I tried and got the following error messages. When I compiled my R as 64bit, I used the SUN ProW compilers. However, gcc seems to being used below as well as missing some information. Thank you in advance, Dongseok > install.packages("rgl") --- Please select a CRAN mirror for use in this session --- *

Dear r-help, I need to draw xyplot() graphs with several regression lines: one line for the whole range of x (the variable on the horizontal axis) and two additional lines for subranges of x. Is it possible to make first regression line (panel.lmline(x,y,...);) to be drawn on the whole graph and regression lines of the subsets to be drawn only over their subsets? I have defined

Hi Dieter and R community: I tried both of these three versions with ylim as suggested, none work: I am getting only single (pch = 16) not overlayed (pch =3) everytime. *vs 1* require(lattice) xyplot(Sepal.Length ~ Sepal.Width | Species , data= iris, panel= function(x, y, subscripts) { panel.xyplot(x, y, pch=16, col = "green4", ylim = c(0, 10)) panel.lmline(x, y, lty=4, col =

Dear R-list, Realising the importance of updating the R base, I tried to compile the source file of R2.2.1 in my machine, but failed. According to "R for Mac OS X FAQ", i've got the basic dependencies which are gcc 3.3 and g77 3.4. ./configure is fine Here are the errors I got from make: >make ... gcc -I../../src/extra/zlib -I../../src/extra/bzip2 -I../../src/extra/pcre