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Hello List, I have been using Sweave for my homework this last quarter and have been very impressed at how much time and effort it saves me. I, however, have run up against a problem which I have not been able to solve using any of the Sweave/LaTeX tricks I know. I work through my homework one problem at a time, typesetting equations and writing R code, etc. and occasionally use

List, I am using the 'tisPlot' function in Jeff Hallman's excellent tis package and was hoping that someone could spare me from having to dig into the code of his 'tisPlot' function. So far as I can tell, the preferred method of controlling the plotting of the x-axis is using the 'xTickFreq' and 'xTickSkip' options. Unfortunately, the where the data ends

All, I just finished the process of build a package for the first time and found it characteristically (for R) very straightforward and well documented. Whenever I deal with open source software I always endeavor to finish the task I have in mind, and upon completing this, I then revisit all of the configurations, customizing as necessary to achieve my goals more fully. The ability to achieve

List, I have a question about why plots sent to certain devices can be of so much worse quality than others. Whenever I plot to x11 or pdf the graphs are of excellent quality. eps is a bit poorer, but of passable quality, and jpeg or tiff are terrible. I tried all manner of parameters, on many versions of R (most major releases from about 2.2 - present) under linux and windows and on a few

List, I am currently producing a series of charts using multiple calls to pdf() but, rather than having ''n'' single plot files, would like them all to go into one ''n''-page pdf file. Would someone be so kind as to explain how, if at all, I might go about doing this from within R? I have only ever previously used devices besides x11 by analogy with printing things

List, Would someone be so kind as to point me to a function that will calculate simultaneous confidence intervals of regression coefficients based upon their distribution as (under the assumption of normal errors, with \mathbf{X} as the design matrix): $\hat{\mathbf{\beta}} \sim N(\mathbf{\beta}, \sigma^2(\mathbf{X}^T\mathbf{X})^{-1})$. 'confint' calculates individual coefficients so

The example at ?pictex does not work (the driver apparently uses 'rotatebox') for me as stated. It did compile after including the graphicsx package. A MWE is at the help page for pictex. I tried to get in touch with Valerio but his email bounced. Probably we want to add a \usepackage{graphicsx} to the help page and try to track down Valerio. Cheers, Kyle This is pdfTeX, Version

Dear List, First off, my deepest gratitude to the Sweave developers: this tool has improved my quality greatly. A question in my work I use \Sexpr{} statements scalar values and the xtable package for all manner of tables. What I'd like to do is to use a vector inline, rather than a whole separate table. Something like: %%%%%%%%%%%%%%%% begin code % Latex junk % Sweave block:

List, I would like to set a variable to hold, say, the size of my plots in a Sweave document. i.e. something like the following in my '.Rnw' file: ============================================================================== smallPlotSize = 4 <<fig1, echo=false, results=hide, height=smallPlotSize, width=smallPlotSize, fig=true>>= dat <- read.table("

...algaard) 38. ggplot 2 - editing in the "panel_1_1" viewport (Pedro Barros) 39. Sending Notes email out of R under windows (popsmelove) 40. Re: adjusting textsize and spacing in mosaic (vcd package) (Richard.Cotton at hsl.gov.uk) 41. multiple page pdf file using pdf() (Kyle Matoba) 42. Re: Trend graph (Greg Snow) 43. Re: multiple page pdf file using pdf() (Peter Dalgaard) 44. Re: superimpose histogram on biplot (Kevin Wright) 45. Re: efficient code - yet another question (Kevin Wright) 46. Re: turning comma separated string from multiple choices into flags (H...

In the course of some work I have been doing for Revolution Analytics I have had the necessity of modifying the plm function so that it would not die halfway through fitting. In particular, I was able to more than halve the runtime (for my particular run) and improve its memory usage with three small modifications: 1.) Replacing throughout apply(X, 2, mean) with colMeans, similarly with