Question: is the part that Ed Merkle is asking about the change in the
expected NAME associated with the output?
He changed a sort of global parameter affecting how many digits he wants any
compliant function to display. So when he asked for a named vector, the
chosen name was based on his request
Dear all
Thanks a lot for your very helpful explanations and suggestions. I
have increased the size of my computer's "swapfile" and this solved my
problem, i.e., R no longer crashes when I work with character string
variables in my large data set (probably until I work with an even
larger data set
The "value" is *not* 975.
It's 975.025.
The results that you're observing, are merely the byproduct of formatting.
Maybe, you should try:
quantile (x, .975, type=4)
Which perhaps, using default options, produces the result you're expecting?
On Tue, Dec 15, 2020 at 8:55 AM Merkle, Edgar C.
Hi Edgar,
I certainly don't think quantile(x, .975) should return 980, as that is
a completely wrong answer.
I do agree that it seems like the name is a bit offputting. I'm not sure
how deep in the machinery you'd have to go to get digits to no effect on
the names (I don't have time to dig in rig
All,
Consider the code below
options(digits=2)
x <- 1:1000
quantile(x, .975)
The value returned is 975 (the 97.5th percentile), but the name has been
shortened to "98%" due to the digits option. Is this intended? I would have
expected the name to also be "97.5%" here. Alternatively, the return
Dear Sirs,
Running the following code with R devel (2020-11-30 r79529):
library(survival)
terms.formula(Surv(time, status) ~ . - time - status, data = lung[,
c("time", "status", "ph.ecog")])
gives:
Warning message:
In terms.formula(Surv(time, status) ~ . - time - status, data = lung[, :
A recent R-devel commit introduces a change in the way non-printable Unicode
characters are shown as an escape code. Whereas large code points were
previously printed using an escape code of 8 hexadecimal digits, with initial
zeros, the present code (tested with R-devel r79623 on Ubuntu Linux) o
Dear list,
Is there any interest in adding a log.p= option to p.adjust() so that it
can accept log-transformed p-values and return log-transformed adjusted
p-values?
I have some functions that, on occasion, return very low p-values. To
avoid underflow in such cases, I allow my users to set l
