Hello all,
I have run a redundancy analysis on Hellinger transformed species abundance
data and environmental variables.
Once I ran the RDA I proceeded to run a permutation on the resulting rda
overall and by "axis" and the outputs did not provide a legend of
significance codes.
Even if none of
On 26/09/2019 9:44 a.m., Richard O'Keefe wrote:
Actually, R's scope rules are seriously weird.
I set out to write an R compiler, wow, >20 years ago.
Figured out how to handle optional and keyword parameters efficiently,
figured out a lot of other things, but choked on the scope rules.
Consider
On 26/09/2019 12:14 p.m., William Michels wrote:
The best summary I've read on the subject of R's scoping rules (in
particular how they compare to scoping rules in S-PLUS) is Dr. John
Fox's "Frames, Environments, and Scope in R and S-PLUS", written as an
Appendix to the first edition of his
The best summary I've read on the subject of R's scoping rules (in
particular how they compare to scoping rules in S-PLUS) is Dr. John
Fox's "Frames, Environments, and Scope in R and S-PLUS", written as an
Appendix to the first edition of his book, An R and S-PLUS Companion
to Applied Regression
Just when I think I’m starting to get the hang of R I run into something that
sends me back to Go without collecting $200.
The working directory seems to be correct when I load an .rda file but it is
not there and it is not in the Global Environment in the upper right hand
window in RStudio.
On 26/09/2019 12:55 p.m., Phillip Heinrich wrote:
Just when I think I’m starting to get the hang of R I run into something that
sends me back to Go without collecting $200.
The working directory seems to be correct when I load an .rda file but it is
not there and it is not in the Global
I found this confusing until I learned about environments. The current state of
the environment that was active at the time the function was defined is
searched, not a frozen copy of the enclosing environment as it existed at the
time the function was defined.
x <- 1 # as it was when f was
Actually, R's scope rules are seriously weird.
I set out to write an R compiler, wow, >20 years ago.
Figured out how to handle optional and keyword parameters efficiently,
figured out a lot of other things, but choked on the scope rules.
Consider
> x <- 1
> f <- function () {
+ a <- x
+ x <-
On Wed, 25 Sep 2019 at 11:03, Francesco Ariis wrote:
>
> Dear R users/developers,
> while ploughing through "An Introduction to R" [1], I found the
> expression "static scope" (in contraposition to "lexical scope").
>
> I was a bit puzzled by the difference (since e.g. Wikipedia conflates the
>
I want to plot maximum and minimum water temperatures on the same axes and
thought I had the correct syntax:
watertemp <- read.table("../../data/hydro/water-temp.dat", header = TRUE, sep
=",")
watertemp$sampdate <- as.Date(as.character(watertemp$sampdate))
watertempsum <- summary(watertemp)
Instead of trying to mix lattice and base functions, you might try using the
formula:
maxtemp+mintemp ~ sampdate
And then: col= c(“red”, “blue”)
Sent from my iPhone, so make sure those quotes are ordinary double quotes.
—
David
> On Sep 27, 2019, at 6:27 AM, Rich Shepard wrote:
>
> I
On 27/09/19 10:27 AM, Rich Shepard wrote:
I want to plot maximum and minimum water temperatures on the same axes and
thought I had the correct syntax:
watertemp <- read.table("../../data/hydro/water-temp.dat", header =
TRUE, sep =",")
watertemp$sampdate <-
On 27/09/19 11:08 AM, David Winsemius wrote:
Instead of trying to mix lattice and base functions, you might try using the
formula:
maxtemp+mintemp ~ sampdate
And then: col= c(“red”, “blue”)
Sent from my iPhone, so make sure those quotes are ordinary double quotes.
Ah-ha! I've learned
Hello,
I have what should be an easy question to answer I hope. I am using
Capscale and anovs.cca in vegan to examine relationship between genetic
distance among individuals to be predicted by several ecological niche
model distance matrices generated from Circuitscape and partialing out
distance
Dear Rui,
Excellent ! Many thanks.
Le mercredi 25 septembre 2019 à 18:50:09 UTC+2, Rui Barradas
a écrit :
Hello,
In your reproducible example you forget to define 'data'.
You should also
set.seed()
The following works.
data <- data.frame(a, x, z, y_obs)
boot.ci.type <-
And it gets weirder still. I have two Macs similarly configured.
One works just fine with polymode no problems. And, the
other is a nightmare. But, they are so similar, I can’t seem to
find what the difference is between them ;o(
From: Rodney Sparapani
Date: Tuesday, September 24, 2019 at
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