similar to: regression to get non-negative parameters

posting the question in r-help@ to get more feedback :-) thanks, Yun-Fang ----- Original Message ----- From: "Yun-Fang Juan" <yunfang at yahoo-inc.com> To: <s-news at wubios.wustl.edu> Sent: Tuesday, December 16, 2003 2:04 PM Subject: [S] plot stacked bar chart in R > Hi, > I am trying to plot a stacked bar chart in R but am not able to find the > documentation.

Hi, I try to use lm to fit a linear model with 600k rows and 70 attributes. But I can't even load the data into the R environment. The error message says the vector memory is used up. Is there anyone having experience with large datasets in R? (I bet) Please advise. thanks, Yun-Fang [[alternative HTML version deleted]]

Hi, I have a two-way anova with unequal cell numbers that I want to analyze. The problem is I don't have individual observations of the data. I only have the sufficient statistics (mean, variance, # of observations) for each cell. Is there any existing function in S-plus that would allow me to do aov() with the sufficient statistics? The table is like G1 G2 G3 G5 G6 T1 T2 T3

All Is there an R command to produce error bars around a plotted point. Crawley's book uses the command error.bar() but my version of R rejects it. Must be an S+ command(?). Thanks REX [[alternative HTML version deleted]]

Dear R users, Please help me on using "mix" function under package "mixdist". My data distribution shows there are two components for the mixture distribution: left part is an exponential and right part is a normal. So I plan to use "gamma" mixture distribution to estimate the parameters. Here is what I am using for the "mix" function. Test<-mix(x,

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Hi, > ----- Original Message ----- >>> ----- Original Message ----- >>>> Hi all, >>>> My recent commit r187027 fixed a simple oversight of forgetting >>>> to >>>> check for __ppc__ (only checking __powerpc__), which broke my >>>> powerpc-apple-darwin8 stage1 tests, since the system gcc only >>>> provided

On Fri, Dec 16, 2011 at 01:51:57AM -0500, David Fang wrote: > Hi, > Thanks for the quick reply again. > >> On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >>> Hi, >>> >>> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >>> have the following test results to share. >>>

[In future, please press reply all as there might be others in the mailing list who can help you] Without a (short) reproducible example, it would be difficult to say. BTW, I think you have mistyped the error/warning message. Does it actually say "cannot compute _correct_ p-value" or "cannot compute _exact_ p-value". See example below. > wilcox.test( 1:3, 1:10 )

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Following the instruction in R website and downloading gcc and g77, I am trying to configure and build R in my Mac laptop, but got some error message that I do not know how to resolve. Do any of you know how to solve this problem? After type ./configure, I got the following message. R is now configured for powerpc-apple-darwin8.3.0 Source directory: . Installation

Hi, For anyone who might be interested, I've thrown together a little page to track my builds of llvm and clang, both release 3.0 and svn-trunk, on powerpc-darwin8. http://www.csl.cornell.edu/~fang/sw/llvm/ I'll update the list of logs each time I svn-update and build. It's nowhere as nice as a real buildbot page, but it's better than nothing. 3.0 still has over 20 test

----- Original Message ----- > > ----- Original Message ----- > >> Hi all, > >> My recent commit r187027 fixed a simple oversight of forgetting > >> to > >> check for __ppc__ (only checking __powerpc__), which broke my > >> powerpc-apple-darwin8 stage1 tests, since the system gcc only > >> provided > >> __ppc__. I was

> ----- Original Message ----- >> Hi all, >> My recent commit r187027 fixed a simple oversight of forgetting to >> check for __ppc__ (only checking __powerpc__), which broke my >> powerpc-apple-darwin8 stage1 tests, since the system gcc only >> provided >> __ppc__. I was wondering if this justifies using simpler macros like >> >> #define

Hi, Thanks for the quick reply again. > On Thu, Dec 15, 2011 at 1:17 PM, David Fang <fang at csl.cornell.edu> wrote: >> Hi, >> >> I've bootstrapped llvm/clang from svn-trunk on powerpc-darwin8 (g++-4.0.1), and >> have the following test results to share. >> Summary below, full log at: >>

18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > Hi, >          For anyone who might be interested, I've thrown together a little > page to track my builds of llvm and clang, both release 3.0 and > svn-trunk, on powerpc-darwin8. > > http://www.csl.cornell.edu/~fang/sw/llvm/ > > I'll update the list of logs each time I svn-update and

On Fri, Dec 16, 2011 at 12:17:32PM -0500, David Fang wrote: >>> These results have far fewer failures than svn-trunk, and are also >>> comparable to bootstrapping with gcc-4.6.2, summarized here: >>> http://paste.lisp.org/display/126363 >>> (Unfortunately, I no longer have the whole build/test log for the gcc46 bootstrap.) >>> This consistency between

On Wed, Jan 18, 2012 at 10:51:38PM +0400, Konstantin Tokarev wrote: > > > 18.01.2012, 02:46, "David Fang" <fang at csl.cornell.edu>: > > Hi, > > ?????????For anyone who might be interested, I've thrown together a little > > page to track my builds of llvm and clang, both release 3.0 and > > svn-trunk, on powerpc-darwin8. > > > >

Dear all, I have another question about fisher.test: Is there any way to save the resulting p-value in a matrix or file after a loop as below? for (i in 1:42) { # testing difference in income(pinc) between people in # (with in1=1) and out (with in1=0) of the program for # group i fisher.test(m$pinc[m$group==i], m$in1[m$group==i], workspace=40000000, hybrid=F)} When I run this loop, there is no

Dear all, I have another question about fisher.test: Is there any way to save the resulting p-value in a matrix or file after a loop as below? for (i in 1:42) { # testing difference in income(pinc) between people in # (with in1=1) and out (with in1=0) of the program for # group i fisher.test(m$pinc[m$group==i], m$in1[m$group==i], workspace=40000000, hybrid=F)} When I run this loop, there is no