Re: [Rd] NIST StRD linear regression
That is not an appropriate way to fit a degree-10 polynomial (in any language, if fitting a degree-10 polynomial is in fact an appropriate statistical analysis, which seems unlikely). On Sun, 30 Jul 2006, Carnell, Rob C wrote: NIST maintains a repository of Statistical Reference Datasets at http://www.itl.nist.gov/div898/strd/. I have been working through the datasets to compare R's results to their references with the hope that if all works well, this could become a validation package. What does it validate? The R user's understanding of numerical methods? All the linear regression datasets give results with some degree of accuracy except one. The NIST model includes 11 parameters, but R will not compute the estimates for all 11 parameters because it finds the data matrix to be singular. The code I used is below. Any help in getting R to estimate all 11 regression parameters would be greatly appreciated. I am posting this to the R-devel list since I think that the discussion might involve the limitations of platform precision. I am using R 2.3.1 for Windows XP. rm(list=ls()) require(gsubfn) That is not needed. defaultPath - my path data.base - http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA; reg.data - paste(data.base, /Filip.dat, sep=) model - V1~V2+I(V2^2)+I(V2^3)+I(V2^4)+I(V2^5)+I(V2^6)+I(V2^7)+I(V2^8)+I(V2^9)+I (V2^10) filePath - paste(defaultPath, //NISTtest.dat, sep=) download.file(reg.data, filePath, quiet=TRUE) filePath - url(http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Filip.dat;) will suffice. A - read.table(filePath, skip=60, strip.white=TRUE) lm.data - lm(formula(model), A) lm.data lm(V1 ~ poly(V2, 10), A) works. kappa(model.matrix(V1 ~ poly(V2, 10, raw=TRUE), A), exact=TRUE) [1] 1.767963e+15 shows the design matrix is indeed numerically singular by the naive method. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] NIST StRD linear regression
RobCar == Carnell, Rob C [EMAIL PROTECTED]
on Sun, 30 Jul 2006 19:42:29 -0400 writes:
RobCar NIST maintains a repository of Statistical Reference
RobCar Datasets at http://www.itl.nist.gov/div898/strd/. I
RobCar have been working through the datasets to compare
RobCar R's results to their references with the hope that
RobCar if all works well, this could become a validation
RobCar package.
RobCar All the linear regression datasets give results with
RobCar some degree of accuracy except one. The NIST model
RobCar includes 11 parameters, but R will not compute the
RobCar estimates for all 11 parameters because it finds the
RobCar data matrix to be singular.
RobCar The code I used is below. Any help in getting R to
RobCar estimate all 11 regression parameters would be
RobCar greatly appreciated.
RobCar I am posting this to the R-devel list since I think
RobCar that the discussion might involve the limitations of
RobCar platform precision.
RobCar I am using R 2.3.1 for Windows XP.
RobCar rm(list=ls())
RobCar require(gsubfn)
RobCar defaultPath - my path
RobCar data.base -
http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA;
Here is a slight improvement {note the function file.path(); and
model - ..; also poly(V2, 10) !}
which shows you how to tell lm() to believe in 10 digit
precision of input data.
---
reg.data - paste(data.base, /Filip.dat, sep=)
filePath - file.path(defaultPath, NISTtest.dat)
download.file(reg.data, filePath, quiet=TRUE)
A - read.table(filePath, skip=60, strip.white=TRUE)
## If you really need high-order polynomial regression in S and R,
## *DO* as you are told in all good books, and use orthogonal polynomials:
(lm.ok - lm(V1 ~ poly(V2,10), data = A))
## and there is no problem
summary(lm.ok)
## But if you insist on doing nonsense
model - V1 ~ V2+
I(V2^2)+I(V2^3)+I(V2^4)+I(V2^5)+I(V2^6)+I(V2^7)+I(V2^8)+I(V2^9)+I(V2^10)
## MM: better:
(model - paste(V1 ~ V2, paste(+ I(V2^, 2:10, ), sep='', collapse='')))
(form - formula(model))
mod.mat - model.matrix(form, data = A)
dim(mod.mat) ## 82 11
(m.qr - qr(mod.mat ))$rank # - 10 (only, instead of 11)
(m.qr - qr(mod.mat, tol = 1e-10))$rank # - 11
(lm.def - lm(form, data = A)) ## last coef. is NA
(lm.plus - lm(form, data = A, tol = 1e-10))## no NA coefficients
---
RobCar reg.data - paste(data.base, /Filip.dat, sep=)
RobCar model -
RobCar
V1~V2+I(V2^2)+I(V2^3)+I(V2^4)+I(V2^5)+I(V2^6)+I(V2^7)+I(V2^8)+I(V2^9)+I
RobCar (V2^10)
RobCar filePath - paste(defaultPath, //NISTtest.dat, sep=)
RobCar download.file(reg.data, filePath, quiet=TRUE)
RobCar A - read.table(filePath, skip=60, strip.white=TRUE)
RobCar lm.data - lm(formula(model), A)
RobCar lm.data
RobCar Rob Carnell
A propos NIST StRD:
If you go further to NONlinear regression,
and use nls(), you will see that high quality statistics
packages such as R do *NOT* always conform to NIST -- at least
not to what NIST did about 5 years ago when I last looked.
There are many nonlinear least squares problems where the
correct result is *NO CONVERGENCE* (because of
over-parametrization, ill-posednes, ...),
owever many (cr.p) pieces of software do converge---falsely.
I think you find more on this topic in the monograph of
Bates and Watts (1988), but in any case,
just install and use the CRAN R package 'NISTnls' by Doug Bates
which contains the data sets with documentation and example
calls.
Martin Maechler, ETH Zurich
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[Rd] R sources: .tgz oder .tar.gz
This is a minor documentation inconsistency: While the R Installation and Administration manual speaks about the file R-x.y.z.tgz, this has to be replaced by R-x.y.z.tar.gz for x 1. Uwe Ligges __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] Warning when indexing data.frame with FALSE
data.frame()[] NULL data frame with 0 rows data.frame()[FALSE] Warning in is.na(nm) : is.na() applied to non-(list or vector) NULL data frame with 0 rows data.frame()[NULL] Warning in is.na(nm) : is.na() applied to non-(list or vector) NULL data frame with 0 rows Is this a bug? I wouldn't have expected the warning in the last two cases. Regards, Hadley __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] Warning when indexing data.frame with FALSE
Sorry, a better example is: data.frame(a=1)[FALSE] NULL data frame with 1 rows data.frame(a=1)[NULL] NULL data frame with 1 rows vs data.frame()[FALSE] Warning in is.na(nm) : is.na() applied to non-(list or vector) NULL data frame with 0 rows data.frame()[NULL] Warning in is.na(nm) : is.na() applied to non-(list or vector) NULL data frame with 0 rows Hadley __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] Any interest in merge and by implementations specifically for so
Hi Tom,
Now, try sorting and using a loop:
idx - order(i)
xs - x[idx]
is - i[idx]
res - array(NA, 1e6)
idx - which(diff(is) 0)
startidx - c(1, idx+1)
endidx - c(idx, length(xs))
f1 - function(x, startidx, endidx, FUN = sum) {
+ for (j in 1:length(res)) {
+ res[j] - FUN(x[startidx[j]:endidx[j]])
+ }
+ res
+ }
unix.time(res1 - f1(xs, startidx, endidx))
[1] 6.86 0.00 7.04 NA NA
I wonder how much time the sorting, reordering and creation os
startidx and endidx would add to this time?
Either way, your code can nicely be used to quickly create the small
integer factors I would need if the igroup functions get integrated.
Thanks!
For the case of sum (or averages), you can vectorize this using
cumsum as
follows. This won't work for median or max.
f2 - function(x, startidx, endidx) {
+ cum - cumsum(x)
+ res - cum[endidx]
+ res[2:length(res)] - res[2:length(res)] - cum[endidx[1:(length
(res) -
1)]]
+ res
+ }
unix.time(res2 - f2(xs, startidx, endidx))
[1] 0.20 0.00 0.21 NA NA
Yes that is a quite fast way to handle sums.
You can also use Luke Tierney's byte compiler
(http://www.stat.uiowa.edu/~luke/R/compiler/) to speed up the loop for
functions where you can't vectorize:
library(compiler)
f3 - cmpfun(f1)
Note: local functions used: FUN
unix.time(res3 - f3(xs, startidx, endidx))
[1] 3.84 0.00 3.91 NA NA
That looks interesting. Does it only work for specific operating
systems and processors? I will give it a try.
Thanks,
Kevin
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[Rd] Choropleths maps of the USA states (PR#9111)
Dear Colegues:
I have tried to reach Ray Brownrigg, [EMAIL PROTECTED]
but my mails have turned back with the following comment
did not reach the following recipient(s):
[EMAIL PROTECTED] on Mon, 31 Jul 2006 12:52:39 +0100
There is no such account in the address
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
I have a problem with the choropleths maps of the USA states=20
In fact, when I use the following code
#
palette(gray(seq(0,.9,len=3D10)))
ordena.estados-c(ALABAMA,ARIZONA,ARKANSAS,CALIFORNIA,COLORADO,
CONNECTICUT,DELAWARE,FLORIDA,GEORGIA,IDAHO,ILLINOIS,INDIANA,=
IOWA,
KANSAS,
KENTUCKY,LOUISIANA,MAINE,MARYLAND,MASSACHUSETTS,MICHIGAN,MINNE=
SOTA,MISSISSIPI,
MISSOURI, MONTANA,NEBRASKA,NEVADA,NEW HAMPSHIRE,NEW JERSEY,
NEW MEXICO,NEW YORK,
NORTH CAROLINA,NORTH DAKOTA,OHIO,OKLAHOMA,OREGON,PENNSYLVANIA,=
RHODE ISLAND,
SOUTH CAROLINA,
SOUTH DAKOTA,TENNESSEE,TEXAS,UTAH,VERMONT,VIRGINIA,WASHINGTON,
WEST VIRGINIA,WISCONSIN,WYOMING)
W-c(1,10,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1=
,1,1,1,1,1,1,1,1,1,1,1,1,1)
mapa.sat-map('state', region =3D ordena.estados,fill=3DT,col=3DW)=20=20
#
That should paint all the states with the same colour except ARIZONA , =
I get the UTAH state also coloured as ARIZONA.
The same thing happens with some other states, I get two states coloured in=
stead of one.
Is there any problem with the way I have made the ranking of states in ord=
ena.estados?
=20
Thank you for any help.
Sincerely
Luc=EDlia Carvalho
[[alternative HTML version deleted]]
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Re: [Rd] Any interest in merge and by implementations specifically for sorted data?
On Sat, 29 Jul 2006, Kevin B. Hendricks wrote:
Hi Bill,
sum : igroupSums
Okay, after thinking about this ...
# assumes i is the small integer factor with n levels
# v is some long vector
# no sorting required
igroupSums - function(v,i) {
sums - rep(0,max(i))
for (j in 1:length(v)) {
sums[[i[[j - sums[[i[[j + v[[j]]
}
sums
}
if written in fortran or c might be faster than using split. It is
at least just linear in time with the length of vector v.
For sums you should look at rowsum(). It uses a hash table in C and last
time I looked was faster than using split(). It returns a vector of the
same length as the input, but that would easily be fixed.
The same approach would work for min, max, range, count, mean, but not for
arbitrary functions.
-thomas
Thomas Lumley Assoc. Professor, Biostatistics
[EMAIL PROTECTED] University of Washington, Seattle
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[Rd] bug in format.default: trim=TRUE does not always work as advertised (PR#9114)
This is a multi-part message in MIME format. --090008060607010208040805 Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit DESCRIPTION OF PROBLEM: Output from format.default sometimes has whitespace around it when using big.mark=, and trim=TRUE. E.g.: # works ok as long as big.mark is not actually used: format(c(-1,1,10,999), big.mark=,, trim=TRUE) [1] -1 1 10 999 # but if big.mark is used, output is justified and not trimmed: format(c(-1,1,10,999,1e6), big.mark=,, trim=TRUE) [1]-1 110 999 1,000,000 The documentation for the argument 'trim' to format.default() states: trim: logical; if 'FALSE', logical, numeric and complex values are right-justified to a common width: if 'TRUE' the leading blanks for justification are suppressed. Thus, the above behavior of including blanks for justification when trim=FALSE (in some situations) seems to contradict the documentation. PROPOSED FIX: The last call to prettyNum() in format.default() (src/library/base/R/format.R) has the argument preserve.width = common If this is changed to preserve.width = if (trim) individual else common then output is formatted correctly in the case above. A patch for this one line is attached to this message (patch done against the released R-2.3.1 source tarball (2006/06/01), the format.R file in this release is not different to the one in the current snapshot of the devel version of R). After making these changes, I ran make check-all. I did not see any tests that seemed to break with these changes. -- Tony Plate --090008060607010208040805 Content-Type: text/plain; name=format.default.fixes.diff Content-Transfer-Encoding: 7bit Content-Disposition: inline; filename=format.default.fixes.diff --- R-2.3.1-orig/src/library/base/R/format.R2006-04-09 16:19:19.0 -0600 +++ R-2.3.1/src/library/base/R/format.R 2006-07-26 15:52:42.117456700 -0600 @@ -37,7 +37,7 @@ small.interval = small.interval, decimal.mark = decimal.mark, zero.print = zero.print, -preserve.width = common) + preserve.width = if (trim) individual else common) ) } } --090008060607010208040805-- __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] Any interest in merge and by implementations specifically for so
Hi Tom,
Now, try sorting and using a loop:
idx - order(i)
xs - x[idx]
is - i[idx]
res - array(NA, 1e6)
idx - which(diff(is) 0)
startidx - c(1, idx+1)
endidx - c(idx, length(xs))
f1 - function(x, startidx, endidx, FUN = sum) {
+ for (j in 1:length(res)) {
+ res[j] - FUN(x[startidx[j]:endidx[j]])
+ }
+ res
+ }
unix.time(res1 - f1(xs, startidx, endidx))
[1] 6.86 0.00 7.04 NA NA
I wonder how much time the sorting, reordering and creation os
startidx and endidx would add to this time?
Done interactively, sorting and indexing seemed fast. Here are some timings:
unix.time({idx - order(i)
+xs - x[idx]
+is - i[idx]
+res - array(NA, 1e6)
+idx - which(diff(is) 0)
+startidx - c(1, idx+1)
+endidx - c(idx, length(xs))
+ })
[1] 1.06 0.00 1.09 NA NA
That looks interesting. Does it only work for specific operating
systems and processors? I will give it a try.
No, as far as I know, it works on all operating systems. Also, it gets a
little faster if you directly put the sum in the function:
f4 - function(x, startidx, endidx) {
+ for (j in 1:length(res)) {
+ res[j] - sum(x[startidx[j]:endidx[j]])
+ }
+ res
+ }
f5 - cmpfun(f4)
unix.time(res5 - f5(xs, startidx, endidx))
[1] 2.67 0.03 2.95 NA NA
- Tom
--
View this message in context:
http://www.nabble.com/Any-interest-in-%22merge%22-and-%22by%22-implementations-specifically-for-sorted-data--tf2009595.html#a5578580
Sent from the R devel forum at Nabble.com.
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[Rd] Bug in title() crashes R (PR#9115)
Hello,
The below reliably crashes R 2.3.1:
plot.new()
title(1:10)
Process R segmentation fault (core dumped) ...
Also, R will crash when these vectors are much smaller, just not as
reliably.
I haven't tried this in on today's snapshot, but didn't see anything in
the changelog that seems to have addressed this.
HTH,
Robert
R.version
_=20
platform i386-pc-mingw32 =20
arch i386 =20
os mingw32 =20
system i386, mingw32=20
status =20
major 2=20
minor 3.1 =20
year 2006 =20
month 06 =20
day01 =20
svn rev38247=20
language R=20
version.string Version 2.3.1 (2006-06-01)
Robert McGehee
Quantitative Analyst
Geode Capital Management, LLC
53 State Street, 5th Floor | Boston, MA | 02109
Tel: 617/392-8396Fax:617/476-6389
mailto:[EMAIL PROTECTED]
This e-mail, and any attachments hereto, are intended for us...{{dropped}}
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[Rd] lazyLoadDBfetch error
I am getting the following output when I try to load R package gmodels under R-devel. This does not occur in R 2.3.1. In searching the R archives it appears that this message regarding lazyLoadDBfetch should not be occurring in recent R releases. I have redownloaded R-devel and gmodels and the problem persists. Ideas? Thanks, Mark require(gmodels) Loading required package: gmodels Error in lazyLoadDBfetch(key, datafile, compressed, envhook) : internal error in R_decompress1 [1] FALSE sessionInfo() R version 2.4.0 Under development (unstable) (2006-06-15 r38348) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] splines tools methods stats graphics grDevices utils datasets base other attached packages: gtools gdataGOstats Category hgu95av2 KEGG multtest xtable RBGL annotate GO graph Ruuid limma 2.2.32.1.21.6.01.4.1 1.10.01.8.11.9.5 1.3-21.8.1 1.10.01.6.5 1.11.9 1.10.02.7.5 genefilter survival rgu34a affy affyioBiobaseRWinEdt 1.10.1 2.26 1.12.0 1.10.01.1.3 1.10.01.7-4 Mark W. Kimpel MD Official Business Address: Department of Psychiatry Indiana University School of Medicine PR M116 Institute of Psychiatric Research 791 Union Drive Indianapolis, IN 46202 Preferred Mailing Address: 15032 Hunter Court Westfield, IN 46074 (317) 490-5129 Work, Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] [R] HTTP User-Agent header
should appear at an R-devel near you...
thanks Seth
Seth Falcon wrote:
Robert Gentleman [EMAIL PROTECTED] writes:
OK, that suggests setting at the options level would solve both of your
problems and that seems like the best approach. I don't really want to
pass this around as a parameter through the maze of functions that might
actually download something if we don't have to.
I have an updated patch that adds an HTTPUserAgent option. The
default is a string like:
R (2.4.0 x86_64-unknown-linux-gnu x86_64 linux-gnu)
If the HTTPUserAgent option is NULL, no user agent header is added to
HTTP requests (this is the current behavior). This option allows R to
use an arbitrary user agent header.
The patch adds two non-exported functions to utils:
1) defaultUserAgent - returns a string like above
2) makeUserAgent - formats content of HTTPUserAgent option for use
as part of an HTTP request header.
I've tested on OSX and Linux, but not on Windows. When USE_WININET is
defined, a user agent string of R was already being used. With this
patch, the HTTPUserAgent options is used. I'm unsure if NULL is
allowed.
Also, in src/main/internet.c there is a comment:
Next 6 are for use by libxml, only
and then a definition for R_HTTPOpen. Not sure how/when these get
used. The user agent for these calls remains unspecified with this
patch.
+ seth
Patch summary:
src/include/R_ext/R-ftp-http.h |2 +-
src/include/Rmodules/Rinternet.h |2 +-
src/library/base/man/options.Rd |5 +
src/library/utils/R/readhttp.R | 25 +
src/library/utils/R/zzz.R|3 ++-
src/main/internet.c |2 +-
src/modules/internet/internet.c | 37 +
src/modules/internet/nanohttp.c |8 ++--
8 files changed, 66 insertions(+), 18 deletions(-)
Index: src/include/R_ext/R-ftp-http.h
===
--- src/include/R_ext/R-ftp-http.h(revision 38715)
+++ src/include/R_ext/R-ftp-http.h(working copy)
@@ -36,7 +36,7 @@
int R_FTPRead(void *ctx, char *dest, int len);
void R_FTPClose(void *ctx);
-void * RxmlNanoHTTPOpen(const char *URL, char **contentType, int
cacheOK);
+void * RxmlNanoHTTPOpen(const char *URL, char **contentType, const
char *headers, int cacheOK);
int RxmlNanoHTTPRead(void *ctx, void *dest, int len);
void RxmlNanoHTTPClose(void *ctx);
int RxmlNanoHTTPReturnCode(void *ctx);
Index: src/include/Rmodules/Rinternet.h
===
--- src/include/Rmodules/Rinternet.h (revision 38715)
+++ src/include/Rmodules/Rinternet.h (working copy)
@@ -9,7 +9,7 @@
typedef Rconnection (*R_NewUrlRoutine)(char *description, char *mode);
typedef Rconnection (*R_NewSockRoutine)(char *host, int port, int server,
char *mode);
-typedef void * (*R_HTTPOpenRoutine)(const char *url, const int cacheOK);
+typedef void * (*R_HTTPOpenRoutine)(const char *url, const char *headers,
const int cacheOK);
typedef int(*R_HTTPReadRoutine)(void *ctx, char *dest, int len);
typedef void (*R_HTTPCloseRoutine)(void *ctx);
Index: src/main/internet.c
===
--- src/main/internet.c (revision 38715)
+++ src/main/internet.c (working copy)
@@ -129,7 +129,7 @@
{
if(!initialized) internet_Init();
if(initialized 0)
- return (*ptr-HTTPOpen)(url, 0);
+ return (*ptr-HTTPOpen)(url, NULL, 0);
else {
error(_(internet routines cannot be loaded));
return NULL;
Index: src/library/utils/R/zzz.R
===
--- src/library/utils/R/zzz.R (revision 38715)
+++ src/library/utils/R/zzz.R (working copy)
@@ -9,7 +9,8 @@
internet.info = 2,
pkgType = .Platform$pkgType,
str = list(strict.width = no),
- example.ask = default)
+ example.ask = default,
+ HTTPUserAgent = defaultUserAgent())
extra -
if(.Platform$OS.type == windows) {
list(mailer = none,
Index: src/library/utils/R/readhttp.R
===
--- src/library/utils/R/readhttp.R(revision 38715)
+++ src/library/utils/R/readhttp.R(working copy)
@@ -6,3 +6,28 @@
stop(transfer failure)
file.show(file, delete.file = delete.file, title = title, ...)
}
+
+
+
+defaultUserAgent - function()
+{
+Rver - paste(R.version$major, R.version$minor, sep=.)
+Rdetails - paste(Rver, R.version$platform, R.version$arch,
+ R.version$os)
+paste(R (, Rdetails, ), sep=)
+}
+
+
+makeUserAgent - function(format = TRUE) {
+agent - getOption(HTTPUserAgent)
+if (is.null(agent)) {
[Rd] building windows packages under wine/linux and cross-compiling.
Had some fun today, and thought it might be a good idea to share and possibly for inclusion to R/src/gnuwin32/README.packages . Wine/linux : while R, ActiveState Perl, mingw all works alright under wine, the blocking issue is Rtool's cygwin dependency. forking (as much of make and sh is forking sub-processes) on posix-on-win32-on-posix currently doesn't work. (http://wiki.winehq.org/CygwinSupport) Cross-compiling: The instruction in R/src/gnuwin32/README.packages essentially works, with one missing detail: R_EXE=/usr/bin/R is also needed. Thus it should be: make R_EXE=/usr/bin/R PKGDIR=/mysources RLIB=/R/win/library \ pkg-mypkg make P_EXE=/usr/bin/R KGDIR=/mysources RLIB=/R/win/library \ pkgcheck-mypkg Hin-Tak Leung __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] building windows packages under wine/linux and cross-compiling.
On Mon, 31 Jul 2006, Hin-Tak Leung wrote: Had some fun today, and thought it might be a good idea to share and possibly for inclusion to R/src/gnuwin32/README.packages . [...] Cross-compiling: The instruction in R/src/gnuwin32/README.packages essentially works, with one missing detail: R_EXE=/usr/bin/R is also needed. Thus it should be: make R_EXE=/usr/bin/R PKGDIR=/mysources RLIB=/R/win/library \ pkg-mypkg make P_EXE=/usr/bin/R KGDIR=/mysources RLIB=/R/win/library \ pkgcheck-mypkg The instructions do work for those who actually follow them! That file says Edit MkRules to set BUILD=CROSS and the appropriate paths (including HEADER) as needed. and the appropriate section of that file is ## === cross-compilation settings = ifeq ($(strip $(BUILD)),CROSS) # Next might be mingw32- or i386-mingw32msvc- or i586- # depending on the cross-compiler. BINPREF=i586-mingw32- # Set this to where the mingw32 include files are. It must be accurate. HEADER=/users/ripley/R/cross-tools5/i586-mingw32/include endif # path (possibly full path) to same version of R on the host system # R_EXE=R and please do note the last two lines. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] Any interest in merge and by implementations specifically for sorted data?
Hi Thomas, Here is a comparison of performance times from my own igroupSums versus using split and rowsum: x - rnorm(2e6) i - rep(1:1e6,2) unix.time(suma - unlist(lapply(split(x,i),sum))) [1] 8.188 0.076 8.263 0.000 0.000 names(suma)- NULL unix.time(sumb - igroupSums(x,i)) [1] 0.036 0.000 0.035 0.000 0.000 all.equal(suma, sumb) [1] TRUE unix.time(sumc - rowsum(x,i)) [1] 0.744 0.000 0.742 0.000 0.000 sumc - sumc[,1] names(sumc)-NULL all.equal(suma,sumc) [1] TRUE So my implementation of igroupSums is faster and already handles NA. I also have implemented igroupMins, igroupMaxs, igroupAnys, igroupAlls, igroupCounts, igroupMeans, and igroupRanges. The igroup functions I implemented do not handle weights yet but do handle NAs properly. Assuming I clean them up, is anyone in the R developer group interested? Or would you rather I instead extend the rowsum appropach to create rowcount, rowmax, rowmin, rowcount, etc using a hash function approach. All of these approaches simply use differently ways to map group codes to integers and then do the functions the same. Thanks, Kevin __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] Bug in title() crashes R (PR#9115)
On 7/31/2006 11:56 AM, [EMAIL PROTECTED] wrote:
Hello,
The below reliably crashes R 2.3.1:
plot.new()
title(1:10)
Process R segmentation fault (core dumped) ...
This was an internal bug in do_title. When the integer vector was
converted to character it wasn't protected, and garbage collection in
the middle of drawing it threw it away. I suppose it could happen with
any title that needed conversion, but the large size of this one made it
more likely that GC would happen. Soon to be fixed in R-devel and
R-patched.
Thanks for the report.
Duncan Murdoch
Also, R will crash when these vectors are much smaller, just not as
reliably.
I haven't tried this in on today's snapshot, but didn't see anything in
the changelog that seems to have addressed this.
HTH,
Robert
R.version
_=20
platform i386-pc-mingw32 =20
arch i386 =20
os mingw32 =20
system i386, mingw32=20
status =20
major 2=20
minor 3.1 =20
year 2006 =20
month 06 =20
day01 =20
svn rev38247=20
language R=20
version.string Version 2.3.1 (2006-06-01)
Robert McGehee
Quantitative Analyst
Geode Capital Management, LLC
53 State Street, 5th Floor | Boston, MA | 02109
Tel: 617/392-8396Fax:617/476-6389
mailto:[EMAIL PROTECTED]
This e-mail, and any attachments hereto, are intended for us...{{dropped}}
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Re: [Rd] Choropleths maps of the USA states (PR#9111)
On 7/31/06, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote:
I have a problem with the choropleths maps of the USA states=20
In fact, when I use the following code
#
palette(gray(seq(0,.9,len=3D10)))
ordena.estados-c(ALABAMA,ARIZONA,ARKANSAS,CALIFORNIA,COLORADO,
CONNECTICUT,DELAWARE,FLORIDA,GEORGIA,IDAHO,ILLINOIS,INDIANA,=
IOWA,
KANSAS,
KENTUCKY,LOUISIANA,MAINE,MARYLAND,MASSACHUSETTS,MICHIGAN,MINNE=
SOTA,MISSISSIPI,
MISSOURI, MONTANA,NEBRASKA,NEVADA,NEW HAMPSHIRE,NEW JERSEY,
NEW MEXICO,NEW YORK,
NORTH CAROLINA,NORTH DAKOTA,OHIO,OKLAHOMA,OREGON,PENNSYLVANIA,=
RHODE ISLAND,
SOUTH CAROLINA,
SOUTH DAKOTA,TENNESSEE,TEXAS,UTAH,VERMONT,VIRGINIA,WASHINGTON,
WEST VIRGINIA,WISCONSIN,WYOMING)
W-c(1,10,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1=
,1,1,1,1,1,1,1,1,1,1,1,1,1)
mapa.sat-map('state', region =3D ordena.estados,fill=3DT,col=3DW)=20=20
#
That should paint all the states with the same colour except ARIZONA , =
I get the UTAH state also coloured as ARIZONA.
The same thing happens with some other states, I get two states coloured in=
stead of one.
Is there any problem with the way I have made the ranking of states in ord=
ena.estados?
I believe that Michigan and Virginia (at least... there may be others)
have more than one polygon. So... you end up not having enough colors
in the list and it wraps around.
I once put together a little recipe including a call to grep() that
handled the duplicate polygons. Try something like:
regions - map('state', namesonly=T)
W - rep(1, length(regions))
W[grep('^arizona', regions, ignore.case=T)] - 10
map('state', fill=T, col=W)
It should also work for the weird states like Michigan and Virginia
(with the appropriate change to the grep call).
Hope this helps...
Chris
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