Dear all,
I am trying to compile the package e1071 (version 1.3-11) with R CMD
INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on
Linux 2.4.9-34smp but keep getting the same error message during
configure :
WARNING: g++ 2.96 cannot reliably be used with this package. Please
On Sat, Jun 07, 2003 at 06:31:22PM +0800, Adaikalavan Ramasamy wrote:
I am trying to compile the package e1071 (version 1.3-11) with R CMD
INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on
Linux 2.4.9-34smp but keep getting the same error message during
configure :
Adaikalavan Ramasamy wrote:
Dear all,
I am trying to compile the package e1071 (version 1.3-11) with R CMD
INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on
Linux 2.4.9-34smp but keep getting the same error message during
configure :
WARNING: g++ 2.96 cannot reliably be used
I am trying to compile the package e1071 (version 1.3-11) with R CMD
INSTALL. I tried with R 1.7.0 on Redhat Linux 2.4.7-10 and R 1.6.2 on
Linux 2.4.9-34smp but keep getting the same error message during
configure :
WARNING: g++ 2.96 cannot reliably be used with this package. Please use
Hello,
I'm working with POSIXct objects, and I found some strange behavior. I'm
trying to extract a 30min time series from a POSIXct vector, and it
seems that R is having problems with daylight saving time:
test
[1] 2002-03-31 01:15:00 CET 2002-03-31 01:30:00 CET
[3] 2002-03-31 01:45:00 CET
Hi,
Suppose I have:
summary(manova(plank.man))
Df Pillai approx F num Df den DfPr(F)
plankton.new[, 1] 1 0.5267 9.8316 6 53 2.849e-07 ***
Residuals 58
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05
On Sat, 2003-06-07 at 18:43, Ko-Kang Kevin Wang wrote:
Hi,
Suppose I have:
summary(manova(plank.man))
Df Pillai approx F num Df den DfPr(F)
plankton.new[, 1] 1 0.5267 9.8316 6 53 2.849e-07 ***
Residuals 58
Take a look at the 'plotmeans' function in the gregmisc library. It will
draw the means and error bars for you, allowing you to connect the means for
the paired control and treated groups with something like this:
R code
# sample source data 10 replicates for each enzyme for treated and control