Displaying 6 results from an estimated 6 matches for "robertzimbardo".
2017 Jul 03
0
R memory limits on table(x, y) (and bigtabulate)
...n may not monitor this list.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Jul 3, 2017 at 1:57 AM, Robert Zimbardo
<robertzimbardo at gmail.com> wrote:
> I have two character vectors x and y that have the following characteristics:
>
> length(x) # same as
> length(y) # 872099
>
> length(unique(x)) # 47740
> length(unique(y)) # 52478
>
> I need to crosstabulate them, which would lead to a table w...
2017 Jul 03
2
R memory limits on table(x, y) (and bigtabulate)
I have two character vectors x and y that have the following characteristics:
length(x) # same as
length(y) # 872099
length(unique(x)) # 47740
length(unique(y)) # 52478
I need to crosstabulate them, which would lead to a table with
47740*52478 # 2505299720
cells, which is more than
2^31 # 2147483648
cells, which seems to be R's limit because I am getting the error message
Error in
2009 Apr 23
1
Failing to print mer object in an RData image
Hi all
I have problems in accessing a mer object called model.01 from a
workspace that was created with R 2.8.1 and saved with save into an
.RData file (on Windows XP or Ubuntu 8.10, don't remember anymore).
Now I want to open it in R 2.9.0 on Ubuntu 8.10. I use
# load workspace
load("name.RData")
which seems to work:
ls() # all objects in there
[1] "all"
2008 Nov 05
1
R 2.8.0 for Ubuntu Intrepid Ibex i386
Hi all
Is there going to be a binary of R 2.8.0 for Ubuntu Intrepid Ibex i386 -
i.e., not just amd 64bit?
Thx,
RZ
[[alternative HTML version deleted]]
2008 Nov 05
1
R 2.8.0 for Ubuntu Intrepid Ibex i386
Hi all
Is there going to be a binary of R 2.8.0 for Ubuntu Intrepid Ibex i386 -
i.e., not just amd 64bit?
Thx,
RZ
[[alternative HTML version deleted]]
2013 Feb 23
1
anova comparisons
I have several linear models on the same data:
m1 <- lm(y ~ poly(x,1))
m2 <- lm(y ~ poly(x,2))
m3 <- lm(y ~ poly(x,3))
What I don't understand is why
anova(m1, m2, m3, test="F")
- yields the same RSS and SS values, but a different p-value from anova(m1,
m2, test="F")
- when it also yields the SAME as anova(m2, m3, test="F")
What am I missing?
Rob