similar to: cor(data.frame) infelicities

Dear all When using Sweave, I'm always hitting the same bump: I want to group repetitive calls in a function, but I want both the results and the function calls in the printed output. Let me explain myself. Consider the following computation in an Sweave document: summary(iris[,1:2]) cor(iris[,1:2]) When using these two calls directly, I obtain the following output: > summary(iris[,1:2])

In a paper I'm writing using Sweave, I make use of lattice graphics, but don't want to explicitly show (or explain) in the article text the print() wrapper I need in code chunks for the graphs to appear. I can solve this by including each chunk twice, with different options, as in <<ortho-xyplot1-code, keep.source=TRUE, eval=FALSE>>= library(nlme) library(lattice)

hi all, Suppose I have four variables (X1,X2,Y1,Y2) I want to calculate conditional correlation of (X1,Y1) given (X2, Y2). How can I do it in R? Thanks Ming Chen

Dear list, Please find below an example of odd behaviour of the by function. It occurs both under GNU/Linux R 2.6.2 and Windows R 2.7.0alpha. Respective sessionInfo()'s are given below. I hope I do not overlook anything. testFactor <- factor(sample(LETTERS[1:6], size = 42, replace = TRUE)) testMatrix <- matrix(rnorm(42 * 6), nrow = 42) testDf <- as.data.frame(testMatrix) by(data

utils::citation() offers the option auto=(NULL|TRUE) to obtain the citations for a package from the package DESCRIPTION file or a CITATION file, as described below: |auto| a logical indicating whether the default citation auto-generated from the package 'DESCRIPTION' metadata should be used or not, or |NULL| (default), indicating that a 'CITATION' file is used if it exists, or

In theory, dlnorm(x, ...) == dnorm(log(x), ...)/x, x>0. Unfortunately, when sd=0, dlnorm and plnorm return NaN, while dnorm returns (if(x != mean)0 else Inf) and pnorm returns (if(x<mean)0 else 1). [A numerical optimization, maxLik{maxLik}, reported the NaNs for me.] help('dlnorm') says, "dlnorm is calculated from the definition (in ?Details?). [pqr]lnorm are based on the

Dear list, "+" (and "-") being defined for difftime class, I expected mean() to return something sensible. This is only half-true : > mean(c(1:5, 5:1),na.rm=TRUE) [1] 3 > mean(as.difftime(c(1:5, 5:1),unit="mins"),na.rm=TRUE) Time difference of 3 mins Fine so far. However : > mean(c(1:5, NA,5:1),na.rm=TRUE) [1] 3 > mean(as.difftime(c(1:5,

format(c(1:2, NA)) gives the last value as "NA" rather than preserving it as NA, even if na.encode = FALSE (which does the 'expected' thing for character vectors, but not numeric vectors). This was already brought up in 2008 in https://bugs.r-project.org/show_bug.cgi?id=12318 where Gregor Gorjanc pointed out the issue. Documentation was added and the bug closed as

Hello, The main reason for resetting the tagbuf in `print.default()` and other entry points to the print routine is that it is currently not reset on exit. Creating a context to reset it on exit to its last value might work. This should be done in the entry points rather than in print-value-rec though, since callers of the latter might write to the tagbuf. Another solution to this problem is

If I do > example(lm) ... > mycoef <- function(object, ...) UseMethod("coef", object) > mycoef(lm.D9) Error in mycoef(lm.D9) : no applicable method for "coef" which is pretty surprising, as coef has a default method. After a bit of digging, this comes from do_usemethod having defenv = environment where the generic was defined */ defenv =

Hello: sort(c('A', 'b', 'C')) seems to produce different answers in R interactive than in "R CMD check", at least under both Fedora 13 and Windows 7 with Windows 7 sessionInfo() copied below: In interactive, the result is c('A', 'b', 'C'); with R CMD check, it is c('A', 'C', 'b'). This produced

Currently S3 objects nested in generic vectors cause the tag buffer to be reset.? This feels sub-optimal for those objects that don't have a print method: > list(a=list(b='hello')) $a $a$b???????????????? ### <<<< notice "$a$b" [1] "hello" > list(a=structure(list(b='hello'), class='world')) $a $b?????????????????? ###

On Mon, Sep 17, 2018 at 5:22 PM, G?bor Cs?rdi <csardi.gabor at gmail.com> wrote: > I would say it is a mis-feature. If the 'x' argument of diag() is a > vector of length 1, then it creates an identity matrix of that size, > instead of creating a 1x1 matrix with the given value: > > ? diag(3) > [,1] [,2] [,3] > [1,] 1 0 0 > [2,] 0 1 0

There were a few "infelicities" that kept the "make distcheck" test from passing. These three patches combine to fix all of them, punting on only one by disabling the install-data-hook rule. >From 7504acedcb71bd80d99abe412e6669b267cade38 Mon Sep 17 00:00:00 2001 From: Jim Meyering <meyering at redhat.com> Date: Fri, 21 Aug 2009 13:37:18 +0200 Subject: [PATCH 1/3]

Hi all, I experience a segfault when calling gplots::heatmap.2(), but only when certain other packages are loaded. I am not sure for the correct place to send this bug report. Should I send it to the package maintainers directly? If R-help is the wrong place, please feel free to direct me to the correct one. I am on debian (testing) linux 64 with the binary R distribution from the

Hi all, I experience a segfault when calling gplots::heatmap.2(), but only when certain other packages are loaded. I am not sure for the correct place to send this bug report. Should I send it to the package maintainers directly? If R-help is the wrong place, please feel free to direct me to the correct one. I am on debian (testing) linux 64 with the binary R distribution from the

Yes, both are rooted in age-old design infelicities (in which, basically, interactive expedience has taken precedence over consistency and generality). Unfortunately, they are quite difficult to rectify, because there are bound to be countless uses of, say, diag(5) as a 5x5 identity matrix which would break if it suddenly meant the 1x1 matrix(5) instead. We'd need a very carefully

Version 3.26 of the survey package is percolating through CRAN. Since the last announcement on this list, of version 3.20, about 18 months ago, the main changes are -- an option to calculate replicate-weight variances from sums of squares around the point estimate rather than from the variance of the replicates ("MSE" style) -- Preston's multistage rescaled bootstrap,

I'm not sure if the gee package is still actively maintained, but I for one find it extremely useful. However, I've come across a few infelicities that I'm hoping could be resolved for future versions. Hope it's okay to list them all in one post! They are: (1) AR(1) models don't fit when clustsize = 1 for any subject, even if some subjects have clustsize > 1. (2) If the

On Sat, Mar 31, 2018 at 12:58:19AM +0000, Eric Wong wrote: > Olly Betts <olly at survex.com> wrote: > > If you're just wanting the 200 newest, it'll be faster not to calculate > > weights, so: > > > > $enquire->set_sort_by_value(0, 1); > > $enquire->set_weighting_scheme(new Xapian::BoolWeight()); > > > > For me, this drops the time